6 Metrics You Might Think are Important But Really Aren’t (And What to Track Instead)

You know all of those metrics you track?

They’re probably worthless.

I’m not saying they have absolutely no value, of course. I’m just saying they’re doing nothing for your bottom line most of the time.

These are the things that you think matter, but don’t.

In other words, you can track them, but don’t rely on them for real dollar value.

The trick is knowing which ones are valuable and which aren’t.

Here’s why some of those “important” metrics don’t really matter. Along with a few actionable ones you should worry about instead.

1. Clicks + Pageviews

We’ve heard it all before. The questions, the egos, the bragging.

How do I drive 100,000 visitors in a month? I need traffic fast!

Here’s how I drove 4,000 visitors a day, you can too with these simple tricks!

*sigh*

It sounds too good to be true, because it is.

Unless you’re getting paid for the pageview, and you want people to bounce instantly and never return, then go for it. Spam your link on Pinterest, forums and Reddit.

But, if you want to be realistic with yourself, clicks on your ads and page views on your content mean nothing if people aren’t either:

  1. Sticking around and reading more on your site
  2. Converting / buying a product or service / signing up for something
  3. Fulfilling the goal you have set on that page for visitors

So, if your clicks went through the roof yesterday like this:

But, your conversions were like this:

And your pageviews were like this:

But your goal completions were like this:

Then what.is.the.point?

Clicks and pageviews are worthless if they don’t lead to conversions.

2. CTR

CTR. The glorified metric that drives everyone from PPC to SERP “growth hackers” crazy.

Look at me, I’ve got a 66% CTR!

Oh cool, how many conversions did that get you? Two out of 4,000 clicks? Make it rain baby!

Ok, on a more serious note, here’s why CTR don’t mean $#!* in the real world:

Take a look at that AdWords table.

The highest converting, highest traffic keyword/ad group has the lowest CTR (by far).

YET… also the highest conversions (by far).

Paying a low bid on the keyword and spending less money = lower positions = more competition = lower CTR.

But, conversions are still sky-high.

The whole account has an average total CTR of 3.49%. That’s “not good.”

Except, the average Cost per Conversion is 5x lower than the average sale revenue.

I’ll take that deal any day of the week.

CTR ain’t the gold standard. I don’t care what your CTR is if it doesn’t bring in conversions.

3. Impressions

Let’s say you own a brick and mortar store. You sell shoes.

It’s launch day and you get 40,000 people to walk in and out of your store that day.

Those ads must be working!

You’re checking ‘the books’ and you see the following sales numbers: $500. Total.

Now do you get it?

Impressions are cool and all.

“Hey, (insertbossesname), our product was seen by 100,000 people today!”

But at the end of the day, they don’t matter if (can you guess what’s next?) they don’t lead to sales, conversions, or goal completions.

4. Total Backlinks

Backlinks are good. They help with ranking metrics and credibility.

But total backlink quantity is over-emphasized.

Constantly we see people worrying about how many links they can get, however they can.

*Queue Oprah Gif: You get a link! You get a link! And you get a link!

If your backlink profile is spammy:

… then those links don’t mean anything.

URL’s with low DA’s that are known for spamming or giving links like it’s candy on Halloween aren’t going to get you to the top of Google (anymore).

Ideally, you want a nice backlink profile from relevant, editorially-based sources that don’t just hand over easy links willy nilly.

kissmetrics backlinks

5. Rankings

Rankings can be awesome. Who doesn’t love being #1 on Google?

We’ve all seen this graph before:

traffic drop-off after first page on googleImage Source

Sounds peachy, doesn’t it?

We simply grind our content to the top ten positions and get the lion’s share of clicks.

But, it’s BS. Just ask Wil Reynolds.

Google is constantly changing. Personalizing their methods, learning about real people, and real human interaction with their service.

SEO rankings are more related to user search history now.

There’s more importance being placed on things like first impressions and brand loyalty in today’s world than there is on keywords and content.

So doing all those little SEO tricks to get you to the #1 spot isn’t going to be as helpful as you think.

AND, #1 on the SERPs doesn’t translate into conversions.

You need a funnel. Not a ranking.

6. A/B Test Results

Most A/B tests fail to provide meaningful insights.

Why?

Because you’re testing your own opinions and assumptions, allowing that pesky biases to ravage your results.

That’s not the only problem, though.

Peep Laja from CXL tested tons of data and experiments and found that A/B testing is worthless if you have less than 1000 conversions. Per month. Minimum.

Welp, that’s disheartening. Unless you’re getting over 1k (minimum) conversions per month, forget A/B testing and the results you got.

They don’t mean anything.

They might look nice at first. But most likely, they’ll regress back to the mean eventually.

Here’s what you should be tracking, instead

Don’t drown in all this negativity just yet. There’s good news, too.

Here are a few metrics to focus on to help make the cash register ring.

1. Funnel Report Data

We just talked about how A/B testing was a waste of time unless you have 1,000 minimum conversions per month.

BUT, you can figure out your conversion trouble spots much faster using funnel report data (courtesy of Kissmetrics).

Funnel reports show you how users actually move through your website.

You can see who performed certain actions, who didn’t perform a desired action, and who skipped certain steps in your funnel (for good or for ill).

You can also track certain steps in your funnel:

So if someone visited, then signed up for a newsletter, then viewed a video, you’d know.

You can then use this data to do things like:

  1. Identify conversion bottlenecks preventing people from joining, signing up, opting-in, or signing on the dotted line
  2. Segment your audience into cohorts to further analyze your funnel
  3. Zoom in on your acquisition funnel to see exactly where and when customers activate

Basically, you can determine how to increase conversions. Reliably. Consistently. Without running a single A/B test.

2. Backlink Quality

High quality backlinks can be hard to get.

You can’t fake ‘em.

They’re a leading indicator, sure. But the best kind.

It’s a measure of performance, telling you (1) how efficient those promotional activities are and (2) if you can expect to see increased traffic in the near future as a result.

For example, here’s what a good backlink profile should look like:

moz open site explorer

#humblebrag

It’s diverse.

We aren’t getting hundreds of links from the same site over and over, as the link quality wouldn’t be as strong or meaningful.

And there are links from other high-quality sites in our industry. Relevance for the win!

But building high-quality backlinks takes an investment.

One survey by Moz found that roughly 37% of business owners spend between $10,000 and $50,000 per month on external link building.

That’s a lot.

We’re not saying you have to invest that much. There is a lot you can do to get better backlinks without dropping that kind of dough.

The point isn’t to just build links. That poor-house mindset is how you end up with the junk.

The point is to look at how you’re getting those links. The campaigns and activities and efforts bringing them in.

Change the strategy, change the end result.

3. ROI

Good old ROI. The gold standard metric.

That no one ever talks about online.

You see all the other stuff here. You might see revenue numbers and customer counts.

However, rarely do you see blog posts diving into the bottom-line numbers that actually count.

Let’s say you get four impressions and one click (and one pageview), with a 0.25%CTR and 0.25% conversion rate.

BUT, you only spend $5 and the buyer converts for 10x your cost per acquisition.

See what I mean? Who gives a crap about any other metric in the end besides ROI.

Now, I’m not saying you should completely ignore optimizing for conversions. Definitely not. Those are extremely important.

Just keep in mind that data lies. High conversion rates aren’t always as promising as they look.

Look at historical data, pinpoint trends, figure out what ROI means for you.

Ask: How does this specific measurement help our company’s growth?

And by growth, we don’t mean impressions, rankings, etc.

Knowing the number of leads each ad campaign is driving is fine. But it’s not good. You can’t stop until you see how much revenue each attributes.

Conclusion

Some metrics matter more than others.

Traffic, clicks, page views, CTR, and… don’t matter as much in the long run. Vanity metrics like these sound amazing on press releases and blog posts and webinars and Growth Hackers and weekly stand-up meetings.

But they don’t help so much when it comes time to run the annual numbers.

You want to think big picture.

Look at your overall funnel. Where are people coming in? What are they doing? Where are they going?

Look at your backlinks to see which drive signups. Links, by themselves, are fine. But the important part is to first identify the ones driving real business actions. And then reverse-engineer which activities are driving the ‘winners’ vs. the ‘losers.’

And focus on the one metric that matters: Money. Moolah. The Big Bucks.

Track fewer, better metrics. The ones that count.

So you can learn faster, iterate faster, and eventually, profit faster.

About the Author: Brad Smith is the founder of Codeless, a B2B content creation company. Frequent contributor to Kissmetrics, Unbounce, WordStream, AdEspresso, Search Engine Journal, Autopilot, and more.

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Thanks Live Chat, Messaging Will Take It From Here

Automation is a funny thing. Too little is the enemy of efficiency. Too much kills engagement.

Think about email. Automated email nurturing campaigns were the answer to individually following up with every single person who downloaded a piece of content from your website. In the name of efficiency, marketers queued up a series of emails via workflows to automatically deliver ever-more-helpful content and insights, gradually increasing the person’s trust in the company and stoking the flames of their buying intent. If at any time they had a question, they could respond to the email and get routed to a person who could help.

But as the number of inbound leads skyrocketed, this system became untenable. The dreaded noreply@company.com address was the solution for scalability. Over time, this set the expectation with buyers that marketers didn’t want to have a conversation with them via email.

Automation made us more efficient, but at the cost of relationships — ultimately defeating the purpose.

Then came live chat, and it felt like a revelation. Buyers were empowered to get answers to their questions in real time from a real person. Better yet, this interaction took place directly on the company’s website — where they were already doing their research.

We started using website chat at HubSpot in 2013. Over the past four years, live chat has facilitated countless conversations between curious prospects and our business. We even created our own live chat product — Messages — to help our customers adopt this model and serve their own prospects better, faster, and directly on the website.

But, just like what happened with email nurturing, at a certain point the system started to strain. According to our usage data, one in every 30 website visits results in a chat. For companies that receive thousands of website visits a day, trying to keep up is daunting.

And similar to how “noreply@company.com” frustrated buyers looking for information via email, customers are again the ones suffering when companies can’t manage the demands of live chat. Recent research found that 21% of live chat support requests go completely unanswered. Even if the buyer gets a response, they can expect to wait an average of 2 minutes and 40 seconds for it. I wouldn’t call this “live” — would you?

Responding slowly (or failing to respond at all) on a channel advertised as “live” is a contradiction in terms. Forcing customers to wait after we’ve set the expectation of immediacy is unacceptable. We can do better.

Today, we’re at the same inflection point we came to with email. What should companies do to accommodate the tidal wave of live chat conversations? Hiring an increasing number of chat coordinators clearly isn’t a scalable answer. But more importantly, apps like Facebook Messenger, WhatsApp, and Slack have changed consumers’ definition of a real time conversation (and also created the infrastructure to support them). If marketers are going to advertise “live” channels — and we must if we want to stay relevant — we need to step up and deliver.

It’s with this in mind that I assert the era of live chat is over. “Conversations” were once synonymous with website chat and incoming phone calls, but in the world of messaging apps and bots, the website is only one small piece of the puzzle. Buyers are thinking beyond the website, but most businesses aren’t.

Buyers’ New Expectations for Business Conversations

Website chat enabled buyers to have conversations with businesses like never before. It was a good start, but just that — a start. Similar to how inbound changed marketing, social changed content discovery and consumption, and conversational search changed SEO, messaging apps have changed how buyers expect to interact with businesses.

Why tether your prospects and customers to your website when they want to chat? Why force them to re-explain their question when they switch channels, or when chat coordinators switch shifts? Why make them wait until the next rep is available to get the information they need right now? This isn’t world-class marketing and customer service even today, and it’ll become even more archaic and frustrating in the years to come.

Think your buyers wouldn’t want to interact with your company via a messaging app? Actually, 71% of consumers globally are willing to use messaging apps to get customer assistance.

content-trends-1-2.png

Even if your prospects fall in the “none of the above” bucket today, they won’t forever. Cutting the data by age foretells the inevitability of messaging apps in a business context over time: The majority of consumers currently between the ages 18 and 34 are willing to use Facebook Messenger or WhatsApp to contact companies for assistance.

content-trends-2-2.png

When communicating with a business, today’s buyer expects that:

  • Conversations happen where they are. That might be the website, but it could also be social media, or Skype, or Slack, or a messaging app.
  • Conversations are portable. Regardless of where a conversation gets started, it should be able to be transferred to any other channel seamlessly. A thread kicked off on live chat should be able to be passed to Facebook Messenger or email without data loss or crossed wires.
  • Conversations have context. Context shouldn’t leave with the person who fielded the initial inquiry. All of a customer or prospect’s historical interactions and information should be attached to a common record which populates instantaneously.

We need new technology paired with automation to live up to our buyers’ expectations and make these types of conversations a reality. On the technology side, live website chat is part of a conversation strategy, sure, but it can’t be the whole strategy. As for automation, marketers got it wrong with email, but we have the opportunity to get it right with chat.

Stop Chatting, Start Having Conversations

At HubSpot, we’ve always been about helping marketers and salespeople adapt to the ever-changing modern buyer. It’s time, once again, to step up and serve our prospects and customers the way they expect — and deserve — to be served.

Fortunately, this is possible today with the right strategy. Businesses need to do the following three things to enable truly valuable conversations at scale:

1) Make it possible for buyers to have conversations with your business where they are.

Create a presence on website chat, messaging apps, social media — wherever your prospects might want to talk.

2) Add an automation layer with chatbots.

Set up bots that immediately respond on each channel (or even proactively kick off the conversation) and are equipped to answer common questions. This eliminates customers’ wait time and provides immediate responses for the majority of queries. Bots put the “live” in “live chat.”

3) Adopt technology that helps bots and human service reps to “tag team.”

When a complex question arises, the right technology can loop in a human chat coordinator, and provide a unified record of everything that’s happened in this interaction as well as the customer’s entire history. This way, the context never gets left behind in the handoff between bot and human, or the switch from one communication channel to another.

Marketing automation used to solely refer to workflows + drip email campaigns. Today, it’s much more than that. The new marketing automation is conversational technology + bots. This is automation that makes us more efficient, but more importantly, more effective for our customers. This is automation that creates relationships instead of frustration.

Today, we announced HubSpot’s acquisition of motion.ai — a platform that enables anyone to build and deploy bots across any messaging channel. With this acquisition, we not only hope to enable marketers, salespeople, and service folks to serve their customers better, faster, and with more context than ever before, but we also intend to create the “all in one” experience our customers have come to rely on.

The only constant in business and consumer behavior today is change — which I know firsthand can feel overwhelming. But you’re not in it alone. As your customers change, HubSpot empowers you to adapt to and surpass their expectations. As your business grows, we grow with you. And when new technology emerges, we build it into the growth stack so you can stay ahead of the curve without the headache of wrangling countless disparate apps.

Live chat is the standard today, but I think we should aspire to do better for our buyers. Now I want to hear from you. Do you think live chat in its current manifestation is dead? Is your company prepared to meet the expectations of today’s buyers, and the buyers of tomorrow?

Send HubSpot a note on Facebook Messenger. Tell me what you think the future of communication between buyers and businesses should be.

Let’s have a conversation.

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How to Ask for a Promotion (and Have Other Tough Conversations With Your Boss)

Last year, my colleagues launched a tool called The Next Five to help people navigate through those times in their career where they’re feeling kind of stuck. You know — when you’re just not sure what the next step is on your career path.

And while many of us think about this stuff from time to time — and maybe even practice the speeches to go with them in the shower or in the car — I don’t think we often verbalize our thoughts on where we want our career paths to go, if we even know ourselves.

So, we did a little research to see how often people are actually asking for promotions, or talking with their managers about the next steps in their career paths. It’s pretty hard to find a ton of hard data on it — if you know of any, please send it our way — but we did find this: The Bureau of Labor Statistics reports that the average tenure for today’s worker is 4.4 years. If you focus on just younger employees, that number halves.

What’s more, 91% of workers born between 1977 and 1997 report going into new jobs with the intent of staying less than three years.

While it sure seems like a jumpy career path is normal, there’s more to be said about the importance of these career discussions. After all, if your manager or employer yourself, which would you prefer: helping your team progress internally, or having them leave for what seems like a better opportunity elsewhere?

And if you’re looking to have this conversation with your boss, keep that question in mind. To help you get the conversation started, let’s take a closer look at why they matter and how you can get the most out of them.

Why Ask for a Promotion? Do Career Path Conversations Even Matter?

Some workplaces look at job-hopping as a phenomenon we just need to accept in this day and age. And they’re probably right … to an extent. I don’t think many industries should expect to return to a time when people stayed at companies for decades. But we might be able to find more longevity out of our roles than we do right now.

Quite frankly, job-hopping sucks for more than just the organization that has to rehire and retrain someone every couple years — it sucks for the employee, too. Yes, maybe they get promotions and raises — in fact, it’s not an uncommon way to make your way up the career ladder. But it also means taking a risk, adjusting to a new team and a new manager — possibly finding out one or both of those are a poor fit — and figuring out the nuances of a workplace and job that you could end up hating.

Worst case scenario? You end up out of work at the end of all that, and you’re back on the interview circuit.

So I think it behooves of all of us to have these conversations about what we want our career paths to look like with ourselves, and our managers. It helps us get closer to the work and life we want, and it helps clue our managers in on how to give it to us.

A Few Helpful Guidelines

Before we jump into the nitty-gritty of these conversations, let’s set some ground rules for how these conversations go. Keep these in mind before you launch a large-scale discussion about your career path.

  1. Think about your relationship with your boss. If you’re on good terms, great — chances are, the door is open and you can be candid about what you see for your career trajectory, or your confusion around it. The best managers are the ones who know how to create or find opportunities that combine your skills, interests, and challenges, so these are some things to outline before the conversation. However, if your relationship with your boss isn’t so splendid, or she’s just not in a decision-making position like this one, look higher. Figure out who the best person is to speak with, even if she works in a different department.
  2. Chat with colleagues who are changing roles. When someone on your team is leaving her role, knowing why can help you determine what you see for your own career path, and perhaps give considerations to possible changes that you didn’t otherwise think of. Plus, if she’s leaving a vacancy as a result, that might be an opportunity for you — find out what the true nature of the role is; then, determine the next steps for applying for it internally, if it’s a good fit.
  3. Be your own hiring manager. Many managers crave a sense of proactivity and the ability to solve problems independently from their teams. Remember what we said earlier about what makes a good manager? By figuring out some of these things yourself — like the types of opportunities that are a truly a strong combination of your skills and interests, as well as the team’s unmet needs — you might be able to create your own promotion and subsequent role. Explain why your idea checks off those boxes and meet with your team or boss to discuss it. But be sure to come prepared with a clear idea of what’s next, and how to plan to execute this development should it be approved.

What Elements Make Up an Effective Career Path Conversation?

I’m gonna put my money where my mouth is and talk about my own experiences with these conversations.

I’ve had career path conversations with many bosses — the last formal one was around March — but I’ve also held them with people on my team. Both have been awkward … sometimes. But both have been totally normal and non-cringe-inducing just as often.

When I look back at all those conversations at a macro-level, the good ones (whether they were about my career or my teammates’) all came down to three elements:

  • Relationship
  • Timing
  • Forethought

1) Relationship

Technically, this shouldn’t matter. You should be able to have productive career path conversations no matter the manager-employee relationship. But it would be naive to think the relationship you have with your boss doesn’t play into how well these conversations go. That’s not to say the closer you two are, the better the conversations go — sometimes the closer you are, the harder it is to have frank conversations.

But the better you know each other, and the more ease you have talking with one another, the more likely you’ll have already sorted out communication styles that work. You’ll just know how to get from point A to point B with less pain and awkwardness, because you’ve done it before.

It also gives you the ability to “read the room,” so to speak. You can tell if something you said is being poorly received or misunderstood. Those soft skills matter when you’re talking about career paths because they can accidentally veer into uncomfortable territory and leave people feeling insecure if the communication is off.

If you don’t already have a strong working relationship, it doesn’t preclude you from pulling off a successful conversation. It just makes the next two items — timing and forethought — all the more important.

It also might help to run a few practice rounds with someone so you can make sure you’re clearly verbalizing what you intend. Former HubSpotter Katherine Boyarsky does this and can’t recommend it enough: “Have a mantra that you can repeat in your head during the conversation that helps center you if you go off on a tangent,” she explains.

Aim to be very clear, direct, and forthright with what you’re looking to do without putting the other party on the defensive.

2) Timing

There have been a few career conversations I’ve had in the past that were ill-timed. It didn’t turn them into an utter disaster, but they just didn’t seem to stick. The most common instances where the timing has been off in my experience have been:

  • My boss didn’t know I wanted to have the conversation/I sprung the conversation on a team member in our 1:1. When it comes to talking about your career path, you can’t expect great results from a conversation in which half the people in the room are unprepared. Give everyone some time to think about this. After all, it’s a massive topic that has a lot of moving parts to consider.
  • We tacked it on to the end of a meeting but didn’t have enough time to finish the conversation. Because your career path is such a massive topic, allot enough time to do it justice. I think career discussions are best when they take place over a series of conversations, so it’s alright if you just have a quick thought once in a while. But if you haven’t had this talk with your boss or employee yet (or it’s been a while), make a separate meeting dedicated to this, and only this.
  • I could tell my boss was distracted due to other sources of stress. This is where that “reading the room” I mentioned earlier comes into play. Even if you’ve pre-planned a career path meeting, sometimes things come up that distract one or both of the participants. If you’re picking up on some body language — or spoken language — that indicates distraction, reschedule the meeting.

3) Forethought

A lot of this post so far has been a 50/50 thing — managers and employees should both be held accountable for this career path stuff. But when it comes to forethought, this lies largely on the employees’ shoulders. We need to think about what we want to do in our career. No one can tell us the answer to: “What do you want to do in five years?

Sure, your manager, a mentor, or your family and friends can all talk you through that stuff, but it does come down to you to take ownership over the direction in which you want your career to go.

So, put some forethought into the ways your career path could take shape before broaching the subject with your manager. Some people tend to have really clear career goals, while others are a little more … floaty. That’s fine. If you find yourself in the “floaty” camp, here’s are a couple things to think about to get your brain going:

First, it’s okay to not know what you want from your career at all times. I tend to bucket my life in quadrants:

  • Relationships (friends, family, love)
  • Career (skill development, promotions, satisfaction from the work I’m doing)
  • Hobbies (beach bumming, ghost stuff)
  • Health (exercise, cooking, happiness, clean home)

Typically, not all of those areas of my life are banging on all cylinders at once. When life is going great, usually three — maybe only two — are rocking and rolling while the rest are in stasis for a bit. Sometimes, that thing that’s in stasis is your career. And that’s fine. You don’t need to be thinking about your career path all the time. But if you feel a general ennui, it might be that too many of those areas of your life are lagging — and one could very possibly be your career.

If that’s the case, ask yourself this …

What does the team look like today, versus a year from now?

First, think about this question hypothetically — assessing gaps that will need to be filled down the line, and aligning them with company goals. Then, talk to other leaders in the company and on your team about where they see the team going in a year, and what kinds of goals people might focus on in the future.

This is where your manager can help you, and where I have seen really successful (and non-awkward) career path conversations begin. If you can get a sense of what the organization’s needs will be over the next 12 months, you can start to see which of those needs you’re interested in helping fulfill — because even if your dream job is X, there’s not much anyone can do for you if the company’s investments are in Y.

Finally, remember that career progress comes from a lot of different places, and that progress is indicated by a lot of different things. It comes from skill development, networking, and aligning with projects that advance both personal and company goals. And all of that takes time.

If we want to benchmark our progress, we need to look at more than just promotions. Instead, we need to focus on whether we’re developing new skills, being given more responsibility and autonomy, putting ourselves in mildly uncomfortable situations that help us get better at stuff (hello, public speaking), working with new people in the organization, being asked for our opinion more often, or being pulled into meetings with people we respect and admire.

These are all really good signs of progress that are hard to formalize, but indicate you’re taking the right steps to get your career on the path you’re aiming for.

What Would an Expert Say About All of This?

I’m glad you asked.

That was all based on my experience — holding career path conversations with team members, and with my own manager. But let’s ask an actual HR professional who has spent a lot of time thinking about this stuff.

I talked to our Senior HR Business Partner Brianna Manning, and asked her for the advice she would give someone who was struggling to hold productive conversations about career advancement. She echoed two of the sentiments we’ve already talked about — preparation, and giving a heads up that you want to have this conversation. One point in particular Manning shared regarding preparation is the importance of establishing career trajectory dialogue from the beginning of your relationship together:

“If your manager is well aware of what direction you want to take your career, they can purposefully plan on assignments and projects that help set you in the right direction. In fact, if you want to follow your manager’s path, specifically, you should be direct and let them know that. Ask them to lunch to talk through their challenges, and learn what kinds of projects they took on to help get the skills they needed for the role.”

If you feel unsure of how to start that conversation because you don’t have that solid relationship yet, she provided some sample language that helps make it less intimidating:

“Try opening with something like ‘I learned about this really great resource to help us make the most of our 1:1s and layer in some career development focus — would you be open to trying it?’ or ‘I want to make sure we bake in time for communication around career development in our 1:1s, can we set aside five minutes for that on the agenda on a weekly basis?'”

But Pierce hit on one other important point in initiating these conversations I would be remiss to gloss over: You have to build trust and credibility to have productive career conversations.

It’s really difficult for your manager to focus on your career path if you aren’t succeeding in your current role. Make sure you’ve got a handle on your responsibilities before setting your sights on the next thing. In some cases, it might be wiser to focus on the “now” of your career path rather than the next turn down the road. As Pierce put it:

“If you demonstrate that you always deliver on current responsibilities, and always try to go the extra mile, you’ll build credibility and trust around your own personal brand. This will open doors for you. Just remember that it all takes time. It can’t happen overnight.”

She emphasized that credibility also comes from owning the follow-through on those career conversations. If your manager has opened up some doors for you, make sure you own your progression by nailing those stretch assignments, introductions, or whatever it is you’ve been given an opportunity to shine doing.

What Should You Expect to Get From These Career Path Conversations?

If you’re expecting a specific result out of one conversation, you’re setting yourself up for failure. You wouldn’t expect your manager to come in and dump a promotion on your lap, so you shouldn’t expect to solve your career destiny in one swoop.

In order for those doors to open, all relevant parties must be envisioning you in a certain role for a few months, at least.

I would say the best results typically come from people that think about their career path often, and have frequent — whether formal or informal — conversations about it.

Most of all, those with the most interesting paths tend to just keep an open mind about the different, jagged, very weird ways we all make our way through our careers.

Need help doing a little soul-searching? Take a few minutes to check out The Next Five.

take our five-year career plan quiz

So You Want to Build a Chat Bot – Here’s How (Complete with Code!)

Posted by R0bin_L0rd

You’re busy and (depending on effective keyword targeting) you’ve come here looking for something to shave months off the process of learning to produce your own chat bot. If you’re convinced you need this and just want the how-to, skip to “What my bot does.” If you want the background on why you should be building for platforms like Google Home, Alexa, and Facebook Messenger, read on.

Why should I read this?

Do you remember when it wasn’t necessary to have a website? When most boards would scoff at the value of running a Facebook page? Now Gartner is telling us that customers will manage 85% of their relationship with brands without interacting with a human by 2020 and publications like Forbes are saying that chat bots are the cause.

The situation now is the same as every time a new platform develops: if you don’t have something your customers can access, you’re giving that medium to your competition. At the moment, an automated presence on Google Home or Slack may not be central to your strategy, but those who claim ground now could dominate it in the future.

The problem is time. Sure, it’d be ideal to be everywhere all the time, to have your brand active on every platform. But it would also be ideal to catch at least four hours sleep a night or stop covering our keyboards with three-day-old chili con carne as we eat a hasty lunch in between building two of the Next Big Things. This is where you’re fortunate in two ways;

  1. When we develop chat applications, we don’t have to worry about things like a beautiful user interface because it’s all speech or text. That’s not to say you don’t need to worry about user experience, as there are rules (and an art) to designing a good conversational back-and-forth. Amazon is actually offering some hefty prizes for outstanding examples.
  2. I’ve spent the last six months working through the steps from complete ignorance to creating a distributable chat bot and I’m giving you all my workings. In this post I break down each of the levels of complexity, from no-code back-and-forth to managing user credentials and sessions the stretch over days or months. I’m also including full code that you can adapt and pull apart as needed. I’ve commented each portion of the code explaining what it does and linking to resources where necessary.

I’ve written more about the value of Interactive Personal Assistants on the Distilled blog, so this post won’t spend any longer focusing on why you should develop chat bots. Instead, I’ll share everything I’ve learned.

What my built-from-scratch bot does

Ever since I started investigating chat bots, I was particularly interested in finding out the answer to one question: What does it take for someone with little-to-no programming experience to create one of these chat applications from scratch? Fortunately, I have direct access to someone with little-to-no experience (before February, I had no idea what Python was). And so I set about designing my own bot with the following hard conditions:


  1. It had to have some kind of real-world application. It didn’t have to be critical to a business, but it did have to bear basic user needs in mind.
  2. It had to be easily distributable across the immediate intended users, and to have reasonable scope to distribute further (modifications at most, rather than a complete rewrite).
  3. It had to be flexible enough that you, the reader, can take some free code and make your own chat bot.
  4. It had to be possible to adapt the skeleton of the process for much more complex business cases.
  5. It had to be free to run, but could have the option of paying to scale up or make life easier.
  6. It had to send messages confirming when important steps had been completed.

The resulting program is “Vietnambot,” a program that communicates with Slack, the API.AI linguistic processing platform, and Google Sheets, using real-time and asynchronous processing and its own database for storing user credentials.

If that meant nothing to you, don’t worry — I’ll define those things in a bit, and the code I’m providing is obsessively commented with explanation. The thing to remember is it does all of this to write down food orders for our favorite Vietnamese restaurant in a shared Google Sheet, probably saving tens of seconds of Distilled company time every year.

It’s deliberately mundane, but it’s designed to be a template for far more complex interactions. The idea is that whether you want to write a no-code-needed back-and-forth just through API.AI; a simple Python program that receives information, does a thing, and sends a response; or something that breaks out of the limitations of linguistic processing platforms to perform complex interactions in user sessions that can last days, this post should give you some of the puzzle pieces and point you to others.

What is API.AI and what’s it used for?

API.AI is a linguistic processing interface. It can receive text, or speech converted to text, and perform much of the comprehension for you. You can see my Distilled post for more details, but essentially, it takes the phrase “My name is Robin and I want noodles today” and splits it up into components like:

  • Intent: food_request
  • Action: process_food
  • Name: Robin
  • Food: noodles
  • Time: today

This setup means you have some hope of responding to the hundreds of thousands of ways your users could find to say the same thing. It’s your choice whether API.AI receives a message and responds to the user right away, or whether it receives a message from a user, categorizes it and sends it to your application, then waits for your application to respond before sending your application’s response back to the user who made the original request. In its simplest form, the platform has a bunch of one-click integrations and requires absolutely no code.

I’ve listed the possible levels of complexity below, but it’s worth bearing some hard limitations in mind which apply to most of these services. They cannot remember anything outside of a user session, which will automatically end after about 30 minutes, they have to do everything through what are called POST and GET requests (something you can ignore unless you’re using code), and if you do choose to have it ask your application for information before it responds to the user, you have to do everything and respond within five seconds.

What are the other things?

Slack: A text-based messaging platform designed for work (or for distracting people from work).

Google Sheets: We all know this, but just in case, it’s Excel online.

Asynchronous processing: Most of the time, one program can do one thing at a time. Even if it asks another program to do something, it normally just stops and waits for the response. Asynchronous processing is how we ask a question and continue without waiting for the answer, possibly retrieving that answer at a later time.

Database: Again, it’s likely you know this, but if not: it’s Excel that our code will use (different from the Google Sheet).

Heroku: A platform for running code online. (Important to note: I don’t work for Heroku and haven’t been paid by them. I couldn’t say that it’s the best platform, but it can be free and, as of now, it’s the one I’m most familiar with).

How easy is it?

This graph isn’t terribly scientific and it’s from the perspective of someone who’s learning much of this for the first time, so here’s an approximate breakdown:

Label

Functionality

Time it took me

1

You set up the conversation purely through API.AI or similar, no external code needed. For instance, answering set questions about contact details or opening times

Half an hour to distributable prototype

2

A program that receives information from API.AI and uses that information to update the correct cells in a Google Sheet (but can’t remember user names and can’t use the slower Google Sheets integrations)

A few weeks to distributable prototype

3

A program that remembers user names once they’ve been set and writes them to Google Sheets. Is limited to five seconds processing time by API.AI, so can’t use the slower Google Sheets integrations and may not work reliably when the app has to boot up from sleep because that takes a few seconds of your allocation*

A few weeks on top of the last prototype

4

A program that remembers user details and manages the connection between API.AI and our chosen platform (in this case, Slack) so it can break out of the five-second processing window.

A few weeks more on top of the last prototype (not including the time needed to rewrite existing structures to work with this)

*On the Heroku free plan, when your app hasn’t been used for 30 minutes it goes to sleep. This means that the first time it’s activated it takes a little while to start your process, which can be a problem if you have a short window in which to act. You could get around this by (mis)using a free “uptime monitoring service” which sends a request every so often to keep your app awake. If you choose this method, in order to avoid using all of the Heroku free hours allocation by the end of the month, you’ll need to register your card (no charge, it just gets you extra hours) and only run this application on the account. Alternatively, there are any number of companies happy to take your money to keep your app alive.

For the rest of this post, I’m going to break down each of those key steps and either give an overview of how you could achieve it, or point you in the direction of where you can find that. The code I’m giving you is Python, but as long as you can receive and respond to GET and POST requests, you can do it in pretty much whatever format you wish.


1. Design your conversation

Conversational flow is an art form in itself. Jonathan Seal, strategy director at Mando and member of British Interactive Media Association’s AI thinktank, has given some great talks on the topic. Paul Pangaro has also spoken about conversation as more than interface in multiple mediums.

Your first step is to create a flow chart of the conversation. Write out your ideal conversation, then write out the most likely ways a person might go off track and how you’d deal with them. Then go online, find existing chat bots and do everything you can to break them. Write out the most difficult, obtuse, and nonsensical responses you can. Interact with them like you’re six glasses of wine in and trying to order a lemon engraving kit, interact with them as though you’ve found charges on your card for a lemon engraver you definitely didn’t buy and you are livid, interact with them like you’re a bored teenager. At every point, write down what you tried to do to break them and what the response was, then apply that to your flow. Then get someone else to try to break your flow. Give them no information whatsoever apart from the responses you’ve written down (not even what the bot is designed for), refuse to answer any input you don’t have written down, and see how it goes. David Low, principal evangelist for Amazon Alexa, often describes the value of printing out a script and testing the back-and-forth for a conversation. As well as helping to avoid gaps, it’ll also show you where you’re dumping a huge amount of information on the user.

While “best practices” are still developing for chat bots, a common theme is that it’s not a good idea to pretend your bot is a person. Be upfront that it’s a bot — users will find out anyway. Likewise, it’s incredibly frustrating to open a chat and have no idea what to say. On text platforms, start with a welcome message making it clear you’re a bot and giving examples of things you can do. On platforms like Google Home and Amazon Alexa users will expect a program, but the “things I can do” bit is still important enough that your bot won’t be approved without this opening phase.

I’ve included a sample conversational flow for Vietnambot at the end of this post as one way to approach it, although if you have ideas for alternative conversational structures I’d be interested in reading them in the comments.

A final piece of advice on conversations: The trick here is to find organic ways of controlling the possible inputs and preparing for unexpected inputs. That being said, the Alexa evangelist team provide an example of terrible user experience in which a bank’s app said: “If you want to continue, say nine.” Quite often questions, rather than instructions, are the key.

2. Create a conversation in API.AI

API.AI has quite a lot of documentation explaining how to create programs here, so I won’t go over individual steps.

Key things to understand:

You create agents; each is basically a different program. Agents recognize intents, which are simply ways of triggering a specific response. If someone says the right things at the right time, they meet criteria you have set, fall into an intent, and get a pre-set response.

The right things to say are included in the “User says” section (screenshot below). You set either exact phrases or lists of options as the necessary input. For instance, a user could write “Of course, I’m [any name]” or “Of course, I’m [any temperature].” You could set up one intent for name-is which matches “Of course, I’m [given-name]” and another intent for temperature which matches “Of course, I’m [temperature],” and depending on whether your user writes a name or temperature in that final block you could activate either the “name-is” or “temperature-is” intent.

The “right time” is defined by contexts. Contexts help define whether an intent will be activated, but are also created by certain intents. I’ve included a screenshot below of an example interaction. In this example, the user says that they would like to go to on holiday. This activates a holiday intent and sets the holiday context you can see in input contexts below. After that, our service will have automatically responded with the question “where would you like to go?” When our user says “The” and then any location, it activates our holiday location intent because it matches both the context, and what the user says. If, on the other hand, the user had initially said “I want to go to the theater,” that might have activated the theater intent which would set a theater context — so when we ask “what area of theaters are you interested in?” and the user says “The [location]” or even just “[location],” we will take them down a completely different path of suggesting theaters rather than hotels in Rome.

The way you can create conversations without ever using external code is by using these contexts. A user might say “What times are you open?”; you could set an open-time-inquiry context. In your response, you could give the times and ask if they want the phone number to contact you. You would then make a yes/no intent which matches the context you have set, so if your user says “Yes” you respond with the number. This could be set up within an hour but gets exponentially more complex when you need to respond to specific parts of the message. For instance, if you have different shop locations and want to give the right phone number without having to write out every possible location they could say in API.AI, you’ll need to integrate with external code (see section three).

Now, there will be times when your users don’t say what you’re expecting. Excluding contexts, there are three very important ways to deal with that:

  1. Almost like keyword research — plan out as many possible variations of saying the same thing as possible, and put them all into the intent
  2. Test, test, test, test, test, test, test, test, test, test, test, test, test, test, test (when launched, every chat bot will have problems. Keep testing, keep updating, keep improving.)
  3. Fallback contexts

Fallback contexts don’t have a user says section, but can be boxed in by contexts. They match anything that has the right context but doesn’t match any of your user says. It could be tempting to use fallback intents as a catch-all. Reasoning along the lines of “This is the only thing they’ll say, so we’ll just treat it the same” is understandable, but it opens up a massive hole in the process. Fallback intents are designed to be a conversational safety net. They operate exactly the same as in a normal conversation. If a person asked what you want in your tea and you responded “I don’t want tea” and that person made a cup of tea, wrote the words “I don’t want tea” on a piece of paper, and put it in, that is not a person you’d want to interact with again. If we are using fallback intents to do anything, we need to preface it with a check. If we had to resort to it in the example above, saying “I think you asked me to add I don’t want tea to your tea. Is that right?” is clunky and robotic, but it’s a big step forward, and you can travel the rest of the way by perfecting other parts of your conversation.

3. Integrating with external code

I used Heroku to build my app . Using this excellent weather webhook example you can actually deploy a bot to Heroku within minutes. I found this example particularly useful as something I could pick apart to make my own call and response program. The weather webhook takes the information and calls a yahoo app, but ignoring that specific functionality you essentially need the following if you’re working in Python:

#start
    req = request.get_json
    print("Request:")
    print(json.dumps(req, indent=4))
#process to do your thing and decide what response should be

    res = processRequest(req)
# Response we should receive from processRequest (you’ll need to write some code called processRequest and make it return the below, the weather webhook example above is a good one).
{
        "speech": “speech we want to send back”,
        "displayText": “display text we want to send back, usually matches speech”,
        "source": "your app name"
    }

# Making our response readable by API.AI and sending it back to the servic

 response = make_response(res)
    response.headers['Content-Type'] = 'application/json'
    return response
# End

As long as you can receive and respond to requests like that (or in the equivalent for languages other than Python), your app and API.AI should both understand each other perfectly — what you do in the interim to change the world or make your response is entirely up to you. The main code I have included is a little different from this because it’s also designed to be the step in-between Slack and API.AI. However, I have heavily commented sections like like process_food and the database interaction processes, with both explanation and reading sources. Those comments should help you make it your own. If you want to repurpose my program to work within that five-second window, I would forget about the file called app.py and aim to copy whole processes from tasks.py, paste them into a program based on the weatherhook example above, and go from there.

Initially I’d recommend trying GSpread to make some changes to a test spreadsheet. That way you’ll get visible feedback on how well your application is running (you’ll need to go through the authorization steps as they are explained here).

4. Using a database

Databases are pretty easy to set up in Heroku. I chose the Postgres add-on (you just need to authenticate your account with a card; it won’t charge you anything and then you just click to install). In the import section of my code I’ve included links to useful resources which helped me figure out how to get the database up and running — for example, this blog post.

I used the Python library Psycopg2 to interact with the database. To steal some examples of using it in code, have a look at the section entitled “synchronous functions” in either the app.py or tasks.py files. Open_db_connection and close_db_connection do exactly what they say on the tin (open and close the connection with the database). You tell check_database to check a specific column for a specific user and it gives you the value, while update_columns adds a value to specified columns for a certain user record. Where things haven’t worked straightaway, I’ve included links to the pages where I found my solution. One thing to bear in mind is that I’ve used a way of including columns as a variable, which Psycopg2 recommends quite strongly against. I’ve gotten away with it so far because I’m always writing out the specific column names elsewhere — I’m just using that method as a short cut.

5. Processing outside of API.AI’s five-second window

It needs to be said that this step complicates things by no small amount. It also makes it harder to integrate with different applications. Rather than flicking a switch to roll out through API.AI, you have to write the code that interprets authentication and user-specific messages for each platform you’re integrating with. What’s more, spoken-only platforms like Google Home and Amazon Alexa don’t allow for this kind of circumvention of the rules — you have to sit within that 5–8 second window, so this method removes those options. The only reasons you should need to take the integration away from API.AI are:

  • You want to use it to work with a platform that it doesn’t have an integration with. It currently has 14 integrations including Facebook Messenger, Twitter, Slack, and Google Home. It also allows exporting your conversations in an Amazon Alexa-understandable format (Amazon has their own similar interface and a bunch of instructions on how to build a skill — here is an example.
  • You are processing masses of information. I’m talking really large amounts. Some flight comparison sites have had problems fitting within the timeout limit of these platforms, but if you aren’t trying to process every detail for every flight for the next 12 months and it’s taking more than five seconds, it’s probably going to be easier to make your code more efficient than work outside the window. Even if you are, those same flight comparison sites solved the problem by creating a process that regularly checks their full data set and creates a smaller pool of information that’s more quickly accessible.
  • You need to send multiple follow-up messages to your user. When using the API.AI integration it’s pretty much call-and-response; you don’t always get access to things like authorization tokens, which are what some messaging platforms require before you can automatically send messages to one of their users.
  • You’re working with another program that can be quite slow, or there are technical limitations to your setup. This one applies to Vietnambot, I used the GSpread library in my application, which is fantastic but can be slow to pull out bigger chunks of data. What’s more, Heroku can take a little while to start up if you’re not paying.

I could have paid or cut out some of the functionality to avoid needing to manage this part of the process, but that would have failed to meet number 4 in our original conditions: It had to be possible to adapt the skeleton of the process for much more complex business cases. If you decide you’d rather use my program within that five-second window, skip back to section 2 of this post. Otherwise, keep reading.

When we break out of the five-second API.AI window, we have to do a couple of things. First thing is to flip the process on its head.

What we were doing before:

User sends message -> API.AI -> our process -> API.AI -> user

What we need to do now:

User sends message -> our process -> API.AI -> our process -> user

Instead of API.AI waiting while we do our processing, we do some processing, wait for API.AI to categorize the message from us, do a bit more processing, then message the user.

The way this applies to Vietnambot is:

  1. User says “I want [food]”
  2. Slack sends a message to my app on Heroku
  3. My app sends a “swift and confident” 200 response to Slack to prevent it from resending the message. To send the response, my process has to shut down, so before it does that, it activates a secondary process using “tasks.”
  4. The secondary process takes the query text and sends it to API.AI, then gets back the response.
  5. The secondary process checks our database for a user name. If we don’t have one saved, it sends another request to API.AI, putting it in the “we don’t have a name” context, and sends a message to our user asking for their name. That way, when our user responds with their name, API.AI is already primed to interpret it correctly because we’ve set the right context (see section 1 of this post). API.AI tells us that the latest message is a user name and we save it. When we have both the user name and food (whether we’ve just got it from the database or just saved it to the database), Vietnambot adds the order to our sheet, calculates whether we’ve reached the order minimum for that day, and sends a final success message.

6. Integrating with Slack

This won’t be the same as integrating with other messaging services, but it could give some insight into what might be required elsewhere. Slack has two authorization processes; we’ll call one “challenge” and the other “authentication.”

Slack includes instructions for an app lifecycle here, but API.AI actually has excellent instructions for how to set up your app; as a first step, create a simple back-and-forth conversation in API.AI (not your full product), go to integrations, switch on Slack, and run through the steps to set it up. Once that is up and working, you’ll need to change the OAuth URL and the Events URL to be the URL for your app.

Thanks to github user karishay, my app code includes a process for responding to the challenge process (which will tell Slack you’re set up to receive events) and for running through the authentication process, using our established database to save important user tokens. There’s also the option to save them to a Google Sheet if you haven’t got the database established yet. However, be wary of this as anything other than a first step — user tokens give an app a lot of power and have to be guarded carefully.

7. Asynchronous processing

We are running our app using Flask, which is basically a whole bunch of code we can call upon to deal with things like receiving requests for information over the internet. In order to create a secondary worker process I’ve used Redis and Celery. Redis is our “message broker”; it makes makes a list of everything we want our secondary process to do. Celery runs through that list and makes our worker process do those tasks in sequence. Redis is a note left on the fridge telling you to do your washing and take out the bins, while Celery is the housemate that bangs on your bedroom door, note in hand, and makes you do each thing. I’m sure our worker process doesn’t like Celery very much, but it’s really useful for us.

You can find instructions for adding Redis to your app in Heroku here and you can find advice on setting up Celery in Heroku here. Miguel Grinberg’s Using Celery with Flask blog post is also an excellent resource, but using the exact setup he gives results in a clash with our database, so it’s easier to stick with the Heroku version.

Up until this point, we’ve been calling functions in our main app — anything of the form function_name(argument_1, argument_2, argument_3). Now, by putting “tasks.” in front of our function, we’re saying “don’t do this now — hand it to the secondary process.” That’s because we’ve done a few things:

  • We’ve created tasks.py which is the secondary process. Basically it’s just one big, long function that our main code tells to run.
  • In tasks.py we’ve included Celery in our imports and set our app as celery.Celery(), meaning that when we use “app” later we’re essentially saying “this is part of our Celery jobs list” or rather “tasks.py will only do anything when its flatmate Celery comes banging on the door”
  • For every time our main process asks for an asynchronous function by writing tasks.any_function_name(), we have created that function in our secondary program just as we would if it were in the same file. However in our secondary program we’ve prefaced with “@app.task”, another way of saying “Do wash_the_dishes when Celery comes banging the door yelling wash_the_dishes(dishes, water, heat, resentment)”.
  • In our “procfile” (included as a file in my code) we have listed our worker process as –app=tasks.app

All this adds up to the following process:

  1. Main program runs until it hits an asynchronous function
  2. Main program fires off a message to Redis which has a list of work to be done. The main process doesn’t wait, it just runs through everything after it and in our case even shuts down
  3. The Celery part of our worker program goes to Redis and checks for the latest update, it checks what function has been called (because our worker functions are named the same as when our main process called them), it gives our worker all the information to start doing that thing and tells it to get going
  4. Our worker process starts the action it has been told to do, then shuts down.

As with the other topics mentioned here, I’ve included all of this in the code I’ve supplied, along with many of the sources used to gather the information — so feel free to use the processes I have. Also feel free to improve on them; as I said, the value of this investigation was that I am not a coder. Any suggestions for tweaks or improvements to the code are very much welcome.


Conclusion

As I mentioned in the introduction to this post, there’s huge opportunity for individuals and organizations to gain ground by creating conversational interactions for the general public. For the vast majority of cases you could be up and running in a few hours to a few days, depending on how complex you want your interactions to be and how comfortable you are with coding languages. There are some stumbling blocks out there, but hopefully this post and my obsessively annotated code can act as templates and signposts to help get you on your way.

Grab my code at GitHub


Bonus #1: The conversational flow for my chat bot

This is by no means necessarily the best or only way to approach this interaction. This is designed to be as streamlined an interaction as possible, but we’re also working within the restrictions of the platform and the time investment necessary to produce this. Common wisdom is to create the flow of your conversation and then keep testing to perfect, so consider this example layout a step in that process. I’d also recommend putting one of these flow charts together before starting — otherwise you could find yourself having to redo a bunch of work to accommodate a better back-and-forth.

Bonus #2: General things I learned putting this together

As I mentioned above, this has been a project of going from complete ignorance of coding to slightly less ignorance. I am not a professional coder, but I found the following things I picked up to be hugely useful while I was starting out.

  1. Comment everything. You’ll probably see my code is bordering on excessive commenting (anything after a # is a comment). While normally I’m sure someone wouldn’t want to include a bunch of Stack Overflow links in their code, I found notes about what things portions of code were trying to do, and where I got the reasoning from, hugely helpful as I tried to wrap my head around it all.
  2. Print everything. In Python, everything within “print()” will be printed out in the app logs (see the commands tip for reading them in Heroku). While printing each action can mean you fill up a logging window terribly quickly (I started using the Heroku add-on LogDNA towards the end and it’s a huge step up in terms of ease of reading and length of history), often the times my app was falling over was because one specific function wasn’t getting what it needed, or because of another stupid typo. Having a semi-constant stream of actions and outputs logged meant I could find the fault much more quickly. My next step would probably be to introduce a way of easily switching on and off the less necessary print functions.
  3. The following commands: Heroku’s how-to documentation for creating an app and adding code is pretty great, but I found myself using these all the time so thought I’d share (all of the below are written in the command line; type cmd in on Windows or by running Terminal on a Mac):
    1. CD “””[file location]””” – select the file your code is in
    2. “git init” – create a git file to add to
    3. “git add .” – add all of the code in your file into the file that git will put online
    4. “git commit -m “[description of what you’re doing]” “ – save the data in your git file
    5. “heroku git:remote -a [the name of your app]” – select your app as where to put the code
    6. “git push heroku master” – send your code to the app you selected
    7. “heroku ps” – find out whether your app is running or crashed
    8. “heroku logs” – apologize to your other half for going totally unresponsive for the last ten minutes and start the process of working through your printouts to see what has gone wrong
  4. POST requests will always wait for a response. Seems really basic — initially I thought that by just sending a POST request and not telling my application to wait for a response I’d be able to basically hot-potato work around and not worry about having to finish what I was doing. That’s not how it works in general, and it’s more of a symbol of my naivete in programming than anything else.
  5. If something is really difficult, it’s very likely you’re doing it wrong.
    While I made sure to do pretty much all of the actual work myself (to
    avoid simply farming it out to the very talented individuals at
    Distilled), I was lucky enough to get some really valuable advice. The
    piece of advice above was from Dominic Woodman, and I should have
    listened to it more. The times when I made least progress were when I
    was trying to use things the way they shouldn’t be used. Even when I
    broke through those walls, I later found that someone didn’t want me to
    use it that way because it would completely fail at a later point.
    Tactical retreat
    is an option. (At this point, I should mention he wasn’t
    the only one to give invaluable advice; Austin, Tom, and Duncan of the
    Distilled R&D team were a huge help.)

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Data, Analytics, Technology, and Digital Marketing

Digital marketingThere was a time when a digital marketing team was considered avant-garde if it could define the costs of paid traffic versus organic traffic. Nowadays, understanding your traffic sources is child’s play. If your team can’t define how and when traffic originates, then you’re dead in the water. Much more is needed. 

Successful digital marketing is no longer about having a high PageRank and sitting back while the inbound leads pile up. There’s too much competition. There are too many companies using the right approaches. Your company must incorporate a multi-faceted approach, one where you embrace a personalized inbound marketing strategy that reaches your customers no matter where they are or what they’re doing. Here are some rules to live by.

Adopt a Big Data Marketing Mindset

You can gather all kinds of data and get nowhere if you don’t have the tools or the knowledge to leverage that data properly. Filling out an excel sheet of customer data won’t help if you can’t put it to use. In fact, it’s a waste of time as the influx of real-time data is virtually impossible to manage with manual processes. Extrapolating, disseminating and enriching that data with the right data enrichment software is critical. The idea is to isolate the data that matters most to your audience and your company. That comes from understanding which data to retain and which data to discard. 

None of this is possible if your digital marketing team doesn’t have the right data enrichment tool. Embracing big data means increasing your interactions with customers along their journey. It means mapping out how an interested prospect becomes a lead and how that lead is supported by your digital marketing team. Increase the number of touch-points along your customer’s journey and you’ll be better positioned to identify the specific data points that matter most. 

Using the Right Technologies

Databox.pngSo, how do you ensure your inbound marketing strategy is continually feeding you with up-to-the-minute information? 

First, be willing to investigate emerging technologies. Online searches with Smartphones and mobile handheld comput

ers surpassed laptop searches years ago. A mobile-friendly website is an absolute must in today’s economy. If you don’t have a mobile-capable website, then you’re ignoring a large portion of your market, a portion your competitors are taking full advantage of. 

Second, match your technology to your audience. A perfect example is employing a messaging app or live chat for a constantly moving customer base. Being accessible for customers on the go through a customer-friendly app helps you gather more data while solidifying your brand. It’s all about increasing customer engagement. The more accessible you are, the more engaged your customer base and the more data you can leverage to win more business. It’s all part of your overall strategy to increase the number of touch-points and interactions with your customers.  

Third, don’t ignore the proven performers. The right email marketing strategy can make all the difference. A video-sharing platform like YouTube is a great source of leads. The right social media forum can put you one-step closer to your audience. Webcasts and podcasts allow you to showcase your knowledge to a broad audience while providing your customers with a platform to ask direct questions.

Adopting a Predictive Analytics Model

You know what your customers like and don’t like. You also know that once they get past a certain point that the odds of them buying increases. Unfortunately, not every customer follows a linear path. Not every customer takes the same step-by-step process to make a purchase. 

You may know what a customer will do once they get to that final step, but do you know the likelihood of them progressing from one step to another based on the actions they take? Do you know why, how, and when that customer moved from one step to the next? Do you know why some customers always seem to move quickly through each of these steps, while others seem to be stuck in the mud? This is where predictive analytics come in. 

With predictive analytics, you’re better able to anticipate the different actions each of your customers will take on their way to making a purchase. If your digital marketing team can use historical customer actions to predict future customer actions, then you’re fully embracing the predictive analytics model. 

A perfect example of predictive analytics in use would include the time a customer spends on a given landing page. The longer they spend on that page, the more likely they buy. That likelihood increases if they download a free brochure, it increases again if they watch your corporate video, and it increases even further if they fill out your lead capture form. Now, if you manipulate the placement of these visual prompts, you might just be able to influence these actions. 

Digital marketing

Personalizing Your Marketing Message 

Again, different customers have different journeys which is why having separate strategies for each of your buyer personas is so important. These buyer personas need different types of information. They provide different kinds of data and they require a different analytics approach. Understanding each of your buyer personas is the first step. Mapping out their journey is the next and personalizing your message is the last. 

Personalizing your marketing message is the holy grail of digital marketing. The more personalized your message, the more you’re able to guide your customer along their journey and influence the decisions they make. That means having a customized content marketing strategy, a separate email marketing approach and specific landing pages and social media channels that tailor to the concerns and needs of each of these buyer personas. In turn, the data that each provide allows you to further improve your inbound marketing strategy. 

The days of running a random digital advertising campaign and relying upon re-purposed content are long gone.  The best digital marketing teams define their buyer personas, map out their buyer’s journey, welcome real-time data and use that data in a predictive analytics model that helps them to influence future customer actions.

If you need an inbound marketing agency capable of implementing a customer-focused marketing strategy, then contact us and request an assessment

Podcasts: Your Next Great Marketing Channel, Or Just a Fad?

When it comes to reaching engaged, relevant audiences, which marketing channels truly shine? Social media? Email? Webinars?

How about podcasts?

“Podcasts?” I can hear you thinking, “you mean those radio shows that were popular in the early 2000s?” Sure, podcasts may have hit critical mass thanks to Apple iTunes and the iPod back in 2004, but new research is showing that small businesses and brands alike are taking another look at the podcast as a formidable marketing tool.

Of course the question is — why podcasts? And why has this technology suddenly re-ignited? Let’s take a closer look:

Podcasts’ Surge in Popularity

According to a recent report from Infinite Dial, 40% of respondents reported listening to a podcast at least once, with 24% doing so monthly, and 15% doing so weekly. Year over year, online radio and podcasts in particular, have shown a growth that simply can’t be ignored. What’s more, according to a separate study from Triton Digital and Edison Research, Americans tuning in to podcasts on a weekly basis has almost doubled since 2013:

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Listeners Are More Receptive to Products and Services

People are tuning in — and so are advertisers. There’s a lot for advertisers to like about podcasts, since almost two-thirds of listeners are more willing to consider products and services they learned about on a podcast. Over half of them believed that the hosts of the podcasts they listen to regularly are users of the products and services they mention on their respective shows. And those respondents reacted much more positively to products and services mentioned on the shows from the host themselves rather than a pre-recorded ad from a company or sponsor.

Just look at what actions listeners took after hearing about a product or service in a podcast:

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In addition to high levels of receptiveness, relevancy and engagement, the kinds of people listening to podcasts are the very users many advertisers want to reach: relatively young, high income and high education levels, according to a survey from Nielsen:

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Now the question becomes — how can brands and companies leverage this audience attraction?

Which Brands are Seeing Success with Podcasts?

One of the biggest points to keep in mind is that no one is going to tune in to a 20 minute commercial about your business. Take eBay, for example. Earlier this summer, Brooklyn-based audio company Gimlet Creative completed a branded podcast series for the auction company called Open for Business. It became the number one business podcast in iTunes when it released in June and talks to create a second season are already underway.

On the surface, it looks like Open for Business has very little in common with eBay itself. Topics include details on how to build a business from the ground up, including: how to hire, how an immigrant can start a business in the U.S., and so on.

Mentions of eBay itself are handled in a very light-touch manner. The podcast does, however, circle back by sharing the true story of a small business owner that found success on eBay. The last episode of the first series focused on the gig economy, which includes getting short term jobs and getting paid from gig-style platforms like Uber, Taskrabbit, Airbnb…and eBay.

The series was a hit — generating an average rating of 4.5 on iTunes and hitting 200% of its download goal.

And it’s not just how-to or curriculum-style podcasts that are getting noticed. GE leverages branded content by using its own sound technology in part of a sci-fi series known as The Message, where cryptographers attempt to decipher an alien message. GE itself isn’t mentioned anywhere in the podcast, but its technology is an integrated part of the storyline.

As part of their digital marketing, General Electric has started a podcast that works well with the audio format.

The Message currently has 5 million subscribers.

You can read more about General Electric’s foray into the digital marketing sphere in our post.

But before you get too excited about the potential of podcasts, it’s worth noting a few downsides.

Measuring Reach: Still In Its Infancy

Currently, the best way to measure how much reach a podcast has is the number of downloads and the number of subscribers to a given channel. Podcasts do not yet have the ability to tell you things like how long people listened or, for example, if someone played a podcast in their car with a group of friends.

What’s more, podcasts don’t correlate the number of downloads to the number of subscribers, so hosts don’t know what percentage of their listeners tune in on a weekly basis, or download an episode. How many people listen one time and then never listen again? No one knows.

Even Apple’s podcast app doesn’t provide statistics or analytics that show what kind of reach the podcast has. So, keep this in mind if you’re looking for measurable marketing gains with podcasts — the information you get is fairly shallow compared to the deep, insightful analytics you get with other marketing channels.

Podcasts Set a Higher Bar for Quality

If you’re looking at starting your own podcast, you can see from the examples above, as well as the top podcasts for your particular industry, that there’s a much higher bar set in terms of quality and consistency than with creating other types of content. Articles like this one may take just a few minutes to read, but with a podcast, you’re asking people to tune in for roughly 20 minutes or so per week – the approximate length and schedule for podcasts in general.

That means you have to commit to a standard of quality and a publishing schedule that’s both dedicated and deeply involved. It’s quite the challenge, to be sure, and many companies — even large ones — simply cannot afford that kind of time investment with so many other digital irons in the fire.

Small and medium-sized businesses, however, can look at podcasts as an opportunity to map out a higher grade of content that not only enthralls and engages listeners, but leaves them wanting more. And although the bar for quality is higher, the receptiveness of the audience and their eagerness to take the actions you want them to take after learning about your product or service is definitely worth it.

And although podcasts have risen and waned in popularity throughout the years, the proliferation of online radio, smartphones and home devices like Google Home and Amazon’s Alexa have made tuning into podcasts even more accessible than in a the past. If all indications are showing increasing growth and user adoption, it’s safe to say that podcasting isn’t just a fad — but like all marketing initiatives, the sooner you start, the sooner you can reap the benefits rather than falling behind and being looked at as an “also-ran” by your potential customers.

Do you use podcasts in your own marketing campaigns? What have your results been so far? Share your thoughts with us in the comments below and let us know what tips you have for fellow podcasters who are looking to get started! We can’t wait to hear from you!

About the Author: Sherice Jacob helps business owners improve website design and increase conversion rates through compelling copywriting, user-friendly design and smart analytics analysis. Learn more at iElectrify.com and download your free web copy tune-up and conversion checklist today!

6 Interview Questions to Assess Emotional Intelligence

Despite what you might have come to beleive after sorting through the internet’s seemingly bottomless slew of articles on the subject, emotional intelligence is more than just a buzzword.

The ability to empathize with others, build lasting relationships, and manage emotions in a healthy way has been proven time and time again to be one of the biggest indicators of workplace and interpersonal success.

Emotionally intelligent individuals can more easily adapt to new environments and relate to new colleagues and clients — crucial skills for anyone working at a marketing agency. People with low levels of emotional intelligence might have difficulty managing relationships and dealing with stress, which could lead to burnout or bigger conflicts down the line.

Among employees who fail to meet expectations during their first 18 months on the job, 23% fail due to low emotional intelligence. That’s the second most prevalent reason new hires fail, following only general lack of coachability.

We know gauging a candidate’s emotional intelligence is pivotal when it comes to hiring the best new talent — but can something so complex be sufficiently evaluated in a brief interview setting?

Some candidates have mastered the ability of seeming emotionally intelligent — responding instantaneously with practiced, too-good-to-be-true responses to classic interview questions, e.g.:

What’s your greatest weakness?
Well, I just care too darn much about my work.

To help you sift through the rehearsed responses and dig deeper into a candidate’s real level of emotional intelligence, we’ve put together the following list of interview questions. Learn what to ask below and how to identify an emotionally intelligent response.

6 Interview Questions to Assess Emotional Intelligence

1) Can you tell me about a time you tried to do something and failed?

Asking a candidate to explain a failed project is not only a great way to see how they cope when things don’t go as planned, it’s also an opportunity to see whether or not they’re comfortable taking full responsibility for their actions.

Look for a candidate who can straightforwardly describe a recent failure without shirking the bulk of the blame on other parties or unfortunate circumstances. Even if some external factors played a hand in the mishap, you want a candidate who is comfortable being held fully accountable, and can discuss even the nitty-gritty details of a failed project with fair-minded focus.

Does the candidate seem like they were able to fully bounce back from the issue without getting defensive? Emotionally intelligent individuals possess an inherent self-confidence that can buoy them through setbacks and lets them assess troubling situations objectively, without harsh self-judgment or resorting to outward frustration.

Be wary of candidates who fixate too much on who or what they blame for the failure. When a project doesn’t work out, the key takeaway shouldn’t be based on blame. Emotionally intelligent people know how to move on and examine a situation without bitterness or resentment clouding their judgment.

2) Tell me about a time you received negative feedback from your boss. How did that make you feel?

One of the most easily recognizable qualities of an emotionally intelligent person is their ability to deal with criticism. People with high emotional intelligence are well-equipped to handle negative feedback without losing stride. They can process even unexpected feedback without letting it damage their self-worth.

That’s not to say negative feedback has no emotional impact on emotionally intelligent employees. People with high emotional intelligence experience emotions like everyone else — they just know how to fully process those emotions with a level head and a clear focus on the facts.

Look for a candidate who can specifically describe the feelings they experienced upon receiving negative feedback, e.g.: “At first I was surprised and a little frustrated by my manager’s comments on the project, but when I looked deeper into the reasoning behind her comments, I realized that I could have definitely given more attention to several key areas. On my next project, I was able to use her feedback to develop a more well-rounded approach.”

A response that acknowledges the specific emotions they experienced and shows an empathic understanding of their manager’s point of view indicates a high level of emotional awareness.

Candidates who say they felt “bad” or can’t really express why the feedback affected them might be less emotionally intelligent. Similarly, if a candidate thinks the feedback was wholly undeserved and doesn’t attempt to understand their manager’s point of view, they might have difficulty stepping outside of their own perspective.

3) Can you tell me about a conflict at work that made you feel frustrated?

Everyone gets frustrated sometimes. It’s how you handle that frustration that really matters.

Hearing how a candidate explains a work conflict can offer some valuable clues into their level of emotional intelligence. Conflicts can stir up a lot of difficult emotions, and asking a candidate to describe a dispute and how they dealt with it can give you meaningful insight into how they manage their emotions and empathize with others.

According to psychologist and author Daniel Goleman, emotionally intelligent people have four distinguishing characteristics:

  • They were good at understanding their own emotions (self-awareness)
  • They were good at managing their emotions (self-management)
  • They were empathetic to the emotional drives of other people (social awareness)
  • They were good at handling other people’s emotions (social skills)

All four of these characteristics are put to the test in conflicts situations. Emotionally intelligent people will be able to explain a conflict situation clearly and objectively, giving a specific run down of how they felt at the time, how they managed those feelings, and how they used social cues from those around them to inform their decisions.

As they explain the conflict situation, consider the following four areas:

  • Can they clearly articulate the emotions they experienced during the conflict? (self-awareness)
  • Were they able to move past any negative emotions and work towards a resolution? (self-management)
  • Do they seem aware of the other person’s motivations and challenges? (social awareness)
  • Were they able to mend the relationship and move past the conflict? (social skills)

4) Tell me about a hobby you like to do outside of work. Can you teach me about it?

Ask the candidate to explain one of their hobbies to you as if you know nothing about it. It can be anything — golf, horseback riding, cookie jar collecting — anything they’re interested in and willing to share details about.

As they explain the hobby, prompt them with questions that force them to simplify, re-explain, and change their communication style to suit your clear lack of understanding. See how they react. Are they getting flustered or frustrated? Are they quick to adapt their communication style to meet your needs?

Emotionally intelligent people remain patient and calm when faced with a communication challenge. They can easily read social cues when their message isn’t clearly getting across, and will deftly pivot their approach to meet the needs of their audience.

5) What would your co-workers say is the most rewarding thing about working with you? What about the most challenging thing?

It takes a deep, well-developed sense of self-awareness (and humility) to recognize what really makes you tick. To gauge how well candidates understand their own strengths and limitations in the workplace, ask them to explain how they think others perceive their positive and not-so-positive qualities.

The question is likely to catch some people off guard, but look for candidates who appear comfortable offering up frank commentary without making excuses or immediately invaliding their co-workers’ perceived criticisms.

6) Can you tell me about a time you needed to ask for help on a project?

Emotionally intelligent people are self-confident without being overconfident. They have a realistic understanding of their own strengths and limitations, and they aren’t afraid to admit what they don’t know. They know that asking for help and collaborating with others is a sign of strength, not weakness.

Be wary of candidates who seem hesitant or embarrassed to admit they need help sometimes. Look for someone who can confidently discuss a time when they sought the help of a colleague due to a gap in their knowledge of a subject.

Emotionally intelligent people will be transparent about their weak points, and will show a real drive to better themselves by collaborating and using all the resources available to them.

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