Caution: Predictive Analytics May Miss One Important Thing

Predictive analytics is, without a doubt, the new big thing in marketing.  It’s how we marketers are putting so-called big data to work to help us find, target, and sell to the right customers at the right time.  I’ve written about this before; any time we rely on technology or process to tell us about our customers’ preferences, habits, or needs, we run the risk of missing out on one critical element of our customers’ decision-making.  Our customers are human and, therefore, somewhat unpredictable.

Many years ago, I worked with a company that created customized news feeds.  Customers would select their areas of interest, and each day, the company would sort items from a range of newswires (yes, this is before social media!) and send each customer a custom collection of articles, press releases, and other news items.

A general concern others and I raised about the trend toward more personalization (which is still ongoing) is that people would miss out on items of general interest.  In those days, when I read the newspaper, I would seek out sections of particular interest to me, but I would also read the front page and often catch other items on my way to my sections.  This exposed me to news, information, and thinking outside my specific area of interest.  In particular, reading the front page gave me a sense of what was collectively considered important (as filtered by an editor, granted, but one whose interest likely was matching the collective interest).  This provided a common understanding of the world and important events of the day.  With an entirely customized newswire (or, in today’s terms, a group of Facebook friends with whom you completely agree), you create your own unique understanding of the world around you, and you become less aware of what is outside your bubble (and in some cases, less able to understand it).

One of our goals as marketers is to influence behavior, particularly toward buying our products and services.  One way to do this is to create some elements of a bubble around the target buyers so they see more of your offerings than anything else and more messages encouraging the lifestyle associated with your offerings.  That creates stronger associations with the promise of the brand and results in brand loyalty.

We observe the actions customers take and focus on the ones that make them most likely to deepen their association with our brand and all of the things for which that brand stands. That creates the customer journey.

Once we know all that, we work hard to influence customers to take the next step on their journey toward becoming a brand loyalist and buying more and more from us.

Dealing with the myriad actions, possible paths, probable journeys, and the wide range of customer tastes and behaviors has been nearly impossible until technology stepped in to give us ways to store and analyze all that data.  Enter big data and predictive analytics.

We now have computer systems that tell us—if a customer has a certain set of tastes and preferences, and then takes a given action (or a series of actions)—what the most effective way to get them to take the next action is.  So we do that.  Then we see many of those customers taking the hoped-for action.

Enhancing the Impact of Predictive Analytics

One of my favorite themes is to remind marketers that your instinct—your intuitive understanding—goes far beyond the analysis of any computer system.  You will not always be right, but your intuition provides a strong sanity check.

For example, your predictive analytics might suggest prospects who end up buying from you always take a specified action several steps prior to purchasing.  This might be true.  But you might also notice there is a large drop-off rate right before that step—only a small number of prospects in your funnel move to that step.  Your analytics don’t tell you this because you’ve told your systems to answer the question of what causes people to buy, so it looks at the outcome and works backward.  It takes human powers of observation to look at the funnel from a different perspective.

I rely on my systems and the analyses they produce to tell me how my programs are working.  I set them up to give me data-driven answers to a variety of questions, including the question of what actions are most influential in converting prospects to paying customers.

But I always look at the data myself.  I look for anomalies.  I look for things that might not be answered by my systems the way I’ve set them up.  I look for things I’ve otherwise overlooked.  Some of those insights have led to opportunities I would not have seen otherwise.

In short, I use my own experienced intuition to make the final call about what is working, what is not, and where I should look next to improve my efforts.

Don’t miss out on this one critical factor.  Don’t let your predictive analytics and automation systems take over your marketing.  There may come a day when intelligent systems can do this for us, but for now, this is your job.  It’s where your value gets added.  Using your own experienced intuition is what makes the difference between good marketing and great marketing.  Don’t give that up.

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Three Ways Data Has Changed the CMO: Two Things to Look Out for and One Glimpse of What’s Next

 

One thing most CMOs seem to agree on is that the availability of data and the ability to process it into information have dramatically shifted the role and effectiveness of marketing in an organization.  This data-centric approach to marketing has had several very positive effects on the function, including:

  • Increased accountability of marketing within an organization.
  • Increased effectiveness of programs with better targeting and knowledge of outcomes.
  • Better understanding of the contribution of marketing, resulting in more powerful CMOs.

The Impact of More and Better Data

Data cuts both ways.  It can help make decisions.  It can show you exactly what is happening in any given operation without introducing bias or opinion.  But it can also show you where you are achieving results and where you are not.  It can open a very clear window into the CMO’s performance, which allows for evaluation in ways that are far more objective than were previously possible.

Robert Carroll (@robcarroll), senior vice president of marketing for Gild, notes that just seven or eight years ago, “Marketing accountability didn’t exist.”  It’s not that there were not metrics, but it was much more difficult to establish hard-data success criteria.  With the rise of both CRM systems and marketing automation systems, the data has become available, and it can be turned into analyses that provide these criteria.

One notable way this has changed the marketing organization is in how results are measured.  With these systems and their underlying data in place, it is far easier to determine the exact outcomes of any given program, often from initial engagement all the way to closed sale.

While some organizations are still learning how to make this work for them, many marketing teams use a range of outcome measures such as engagement or conversion to determine everything from cost of sales to whether programs have targeted the right market.

This has also given rise to an opportunity to shift the way marketers operate.  The availability of hard data showing the effectiveness of specific activities and the speed with which that data becomes available allow marketers to try many different hypotheses about which specific items—such as target audiences, content pieces or messages—will be most effective in achieving any given objective.  It lets marketers do the kind of testing and retesting that makes success possible in experimental sciences (such as lab experiments) or in manufacturing design (such as rapid prototyping).

The data and systems are also helping marketers understand media in ways that our profession had only dreamed of.  We can tell exactly which media are most effective to carry our messages and reach our desired target.  Carroll notes, “Email is still the most effective media for outreach.”  But he also has seen a rise, especially with the increasing number of Millennials in both marketing organizations and as members of our target audiences, in the effectiveness of what we might call old-fashioned outreach methods.

“Most Millennials are not used to receiving a telephone call or a postal mailer,” Carroll says. “The sheer novelty of the outreach method is starting to show some unexpectedly positive results.”

While accountability and measurement, in and of themselves, are generally considered good things.  The result of this new level of accountability and the success that has accompanied means that CMOs are gaining more power in the organization.  Now that it is easier to quantify contribution, it’s also easier to show the exact effect the marketing organization has had on the overall business.

As a result, Carroll points out, “More and more, CMOs are becoming CEOs.”

In my own opinion, this also has the potential to result in organizations that are more focused on serving their markets and building better customer relationships.  It certainly will create a different kind of organization than those that followed the historical trend and were led by CFOs or operational executives.

Data Caution!

So far, it’s starting to sound like the rise of the data-based marketer has brought incredibly positive changes and garnered promotions for CMOs.  But the rise of data is also fraught with possibilities to go awry for CMOs:

  • Measurement measures failure just as effectively as it measure success.
  • Data can mislead as easily as it can reveal.

CMOs have jumped on the data bandwagon, and it is, without a doubt, changing their careers.  But where marketers were once able to explain away failure of programs with everything from rebranding to fancy footwork, the ability to look at the data can expose exactly where and why programs failed.  John Philpin, a serial CEO and author of Beyond Bridges, says “Marketers are being found out.”

Philpin also expresses an opinion common to many of us:  “Marketing is as much art as science.”  It’s hard to say that just because a program failed, and we can pinpoint the source of that failure, that the error did not lie in our approach, strategy, judgment, or other human-created idea that was an assumption of the program.

Data can also mislead.  There’s an old saying that the numbers (if you’re an accountant, or the analysis if you’re a statistician) can say whatever you want them to say.  We see this every day in social media where those with specific points of view create charts that appear to be authoritative but are clearly designed to lead the viewer to specific conclusions that benefit the creator.  This happens not just with political pundits, but with marketers as well. We would love to convince the entire world that it has the exact problem we can solve.  And then, of course, sell them the solution.

The data on which we rely for measuring our own success and for proving our success to our organization suffers from the same limitation.  It can be used to show the kind of outcomes we want to believe we have achieved and can be manipulated to hide the outcomes we know will not lead to proving our own effectiveness.

These two concerns—the exposure of failure and the inclusion of human judgment—along with the ability of data to mislead the reader show the limits of reliance on data as the sole measure of success and accountability for a CMO.  It is incumbent upon the CMO to know when data will be useful, how it is most useful, and when to rely on it as a measure of success.

What’s Next for CMOs and Data?

CMOs are seeing the opportunities brought by an increased ability to analyze data and are seeking ways to both expand data access and analysis and find more effective ways to understand and use data.

We’ve all heard about the rise of so-called big data, which Carroll calls “too buzzy” and Philpin calls “a misnomer.  Philpin goes on to add, “Big data is about the relationship among the data—not the data itself.”

Data gets “big” when there’s lots of it, notably more than traditional databases can handle. But it is just this ability to store and analyze unstructured and often unrelated data that can provide insights into our markets and our customers in ways we are only beginning to see.

Carroll sees how the mass of unrelated data Gild is pulling together has started to show them how best to reach their audience, such as where telephone and postal mail can be effective.  He also sees a bigger picture.  “Prepare to be disrupted,” he says, “and all of that data can point to a potential disruptor of your business.”  Since all businesses are potential targets of disruption, it seems like a valuable use of data.

I also agree with Philpin’s answer to my question, “Have you seen big data work in a marketing effort?”  He responded, “Squirrel!”  Staring at data for too long can distract you and lead you to conclusions that are mere mirages.  You start to see things that are just not really there.

More and better data and data analysis are critical to the future of marketing.  Even more critical, however, is the human ability to know how, when, and where to use that data.

Knowing how to turn data into useful information will become more and more important to the success of marketing organizations—and the CMO.

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Escape Social Media FOMO : Ask the One Right Question

If your company or brand is trying to have a presence in every social media outlet possible, you might have social media FOMO (fear of missing out).  But fear not, there is a cure, and unlike consumer FOMO, you don’t need to stop marketing completely.

“Don’t I have to be on every social media outlet?  How will I find my prospects and customers?”

If you’re asking this question, you probably already have FOMO.  You can escape FOMO with one simple question:

“Is this the media in which my prospects prefer to establish relationships?”

EAT24, in what is now a well-publicized move (much to their benefit), recently broke up with Facebook.  If you haven’t done so already, you should read their tongue-in-cheek-but-entirely-serious rationale as well as Facebook’s response.

What they really are saying is they don’t believe social media (specifically Facebook, but this applies to any social media) is about blasting out ads to their fan base.  Rather, it is about establishing relationships and raving fans.  They conclude, given that Facebook allows them very limited organic reach, that they cannot succeed in engaging their fans and building relationships (even those based on sushi porn) in this particular media.

Will this cost them exposure?  Yes.  And while I have no inside knowledge of their media strategy, it’s easy to conclude there are other media which are more effective for their prospects.

They could buy more exposure on Facebook, but it’s also obvious that the amount and depth of engagement is simply not worth it—there are better places to spend that marketing budget.

Applying the test above, it becomes clear their customers and prospects don’t really prefer to build relationships on Facebook, so it’s not worth spending the time and money.

In another recent high-profile move, OKCupid strongly urged its customers not to use the Firefox web browser on their site due to the homophobia of Brendan Eich, the now former head of Mozilla, the organization that publishes Firefox.  Given Firefox’s 10.5% market share (source: netmarketshare.com April 2, 2014), this could be a risky move.

Firefox isn’t a social medium, but it is an important means of accessing OKCupid’s services (and every other service online).  OKCupid is making two statements with this action:

  1. their customers and prospects care about equality and will act on that belief, and
  2.  it’s easy to engage with them using another browser (Chrome, Safari, etc.).

OKCupid clearly believes that once the information about Eich’s homophobia is known, Firefox is not where its prospect and customers will prefer to engage so it does not feel the need to be easily available in every browser.

Back to your brand:  How much time and effort are you investing in making sure you are available everywhere—on every browser, every social media outlet, and everywhere else? Are these time and budget investments well spent?  Do they have the expected or needed ROI?

You know who your customers are.  You know which prospects you are trying to target. Make sure you’re spending your time and money doing what they need you to do to build those relationships.

So before making an investment in a new media outlet, ask yourself:  Is this the medium in which my prospects prefer to establish relationships?

It’s a surefire cure for your FOMO.

Customer Service Culture Keeps Customers Coming Back

Best Customer Service

Below are  examples  of two very different customer service cultures.  Which would you prefer? Let’s say you have to bring your car in for repair.  The mechanic diagnoses the problem. Would you choose:

A)  The shop where the mechanic tells you:  “This is a simple issue.  We fix these all the time.  It’s not going to be any problem at all.  Your car will be good as new in a few hours.  Just go about your business, and I’ll call you when it’s ready.” or

B)  The shop where the mechanic tells you, “Your car’s coolant system has three leaks in different hoses.  The hoses are easy to access, and I have replacements in stock.  It will take me two or three hours to replace the hoses and test them to be sure they are working.  I’ll call you as soon as I’m done.”

If you’re like me, not only do you prefer option (B), but if you run into the mechanic in option (A), you’re likely not to come back (and maybe not even leave your car in the first place).

The reason is we don’t like to be dismissed, and we don’t like condescension.  The mechanic in option (A) was condescending and a bit insulting. She assumed we not only have no idea how our car works but that we don’t care to know and will trust her implicitly. The mechanic in option (B) showed respect for our knowledge, ownership of the car, and likely, our time.

Is your company’s customer service  insulting your customers without even knowing it?

I’ll give you another example of good and bad customer service.  Recently, I contacted technical support for two different software products.  Both are websites that run SaaS products.  Both issues were simple ones that required little explanation and should have been easy to identify as issues (I can’t say how hard they would be to fix).

Company 1 responded like this:

We really appreciate you bringing us this kind of issue affecting our software’s performance.  Rest assured our developers are fully aware of the changes and the glitches that occurred after the software update.  They have made these adjustments their top priority to ensure our software is as stable as possible.

Thank you for your patience and understanding during this time.

Company 2 responded like this:

Thanks so much for writing in!  This is a great question, not too odd at all! 🙂  I’m afraid there isn’t a great solution for this at the moment.  Sorry about that. 🙁  We haven’t figured out a great way for it to know to re-look for the image and description if nothing shows up at first.  Great idea though, and we definitely see the value of it.

Sorry I don’t have a better answer for you on that one.  Is there anything else I can do to help or any questions I can answer?

I’m guessing you know which one I thought was well-done and which I thought was disingenuous

Company 1’s response is more troubling than just a dismissive response.  It points to a customer service culture that assumes customers want reassurance and kind words above all else.  It suggests that the company’s customer service protocol has guidelines or even templates that advance the idea that customers are to be dealt with and dismissed as quickly as possible.

This was reinforced after my follow-up question asking if they knew about the specific issue and might be working on it.  I was told there are many issues on which the developers are working and that I could be certain they would be informed of this one.  Further reinforcing the dismissive approach, five days later the company announced an update that resolved the specific issue.  I have to assume someone there knew that this update was coming yet failed to communicate that to me.

Company 2’s response points to a customer service culture of openness and honesty.  Telling me that there is “no great solution” admits the software has shortcomings and just can’t do everything all the time.  This is true of all products of all kinds.  Being direct about the limitations and aspirations of your product shows both honesty and confidence in your ability to deliver value to your customer.

My cultural assumptions were reinforced on follow-up exchanges, where I offered an idea for a solution, and an interesting discussion on how to best get the specific value I needed from the product ensued.

Evaluating customer service

Far too many companies evaluate the performance of technical support or customer service success on how quickly issues can be resolved and how friendly the language of the company’s representative is.  Both of these measures lead the customer service teams to shorten their responses, use more reassuring and friendly (not honest and direct) language, and to be dismissive of customer issues in the hope they will accept answers such as those above from Company 1 and go away.

But customers are evolving the other way.  Customers demand more details and honestly from companies, as well as more and more transparency.

In order to meet the needs of this evolving customer, companies must also change their customer service culture and the metrics that support it.  For example, rather than measuring duration of interactions, you might measure how many interactions it takes for the customer to consider the issue resolved.  You might also want to measure how much progress each interaction made toward resolving the issue (if it makes no progress, you are wasting time and angering your customer).  Your metrics should always focus on what the customer perceives as progress and what your customer perceives as a resolution.

Is your company’s customer service  culture dismissing and alienating your customers?

Try acting like a customer with a problem for a day, and go find out.  Then tell us your story in the comments.
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Investing in Your Customer (to Avoid Customer Churn)

I had lunch with a friend recently who ran customer success for a SaaS  company.  Customer success in the SaaS business is typically responsible for handling customer support and service to build renewals when they come due while avoiding customer churn (customers who do not renew).

As we discussed the issues surrounding delivering a great customer experience and handling renewal sales, he commented that his biggest surprise was how much customer churn hurt his business.  He noted that every percentage point increase in churn had a multiplier effect on the top line for the business.

I had lunch with a friend recently who ran customer success for a SaaS  company.  Customer success in the SaaS business is typically responsible for handling customer support and service to build renewals when they come due while avoiding churn (customers who do not renew).

I’d be repeating myself if I included a rant on how keeping customers coming back is the only way to realize the return you expect on your investment in customer acquisition.  So instead, let’s talk about investing and how you can apply some very simple investment concepts to your marketing ROI.

Let’s talk bonds to demonstrate customer churn.

I know:  bonds are much less exciting than stocks when it comes to investing, but if you’ve listened to any of the decent advice out there, you probably have a reasonable percentage of your portfolio invested in bonds.

Here’s the thing about bonds:  they provide you with an income stream.  You expect the issuer to pay the coupon on the bond (the debt payment) at the scheduled interval. The market places a value on the bond that is largely based on the dollar amount of those coupon payments, the time over which they will be paid, and the current market interest rates.  If all goes well, you invest a lump sum and get paid back with interest over time.

Sometimes, all does not go well.  I hope it’s rare for your portfolio, but defaults happen. Companies (sometimes even governments) fail to make the coupon payments.  When this happens, you lose your money.  Yes, it’s part of the risk of investing, but it also means your money is gone.  Not exactly the outcome you wanted.

Connecting bonds, marketing, and churn.

Marketers have been talking about a concept called “customer lifetime value” for the past few years.  Whether you are in a business that depends on subscribers or repeat customers, you can look at your customer the same way you look at a bond:  you pay some amount up front (your acquisition cost), and you get a revenue stream that comes in at predictable intervals over time.  As with the coupon payments on a bond, you can use the risk of the market and net present value formulas to determine the value of a customer’s revenue.

But sometimes customers don’t come back or don’t renew.  The difference is that this happens at a much higher rate than bond defaults.  For some SaaS software companies, customer churn (the rate of non-renewals) can be as high as 30% annually.

Let me show you what this does to your portfolio or your top line in marketing terms.

For the sake of simplicity and illustration, let’s assume you have 1,000 customers today, and those customers are paying you $100 per month for your service.  Let’s also say you are a fast growing company, hitting growth rates of 50% annually.  Here’s what churn (or customers not coming back) does to your business over three years.

MRR - Churn Rates
Click on chart to enlarge.

On the chart above, the green line shows monthly recurring revenue (MRR) growth over three years, assuming there is no churn.  The yellow line shows the same growth rate, but assumes 10% churn.  The red line shows the same growth rate, but assumes 30% churn.

If you lose 30% of your customers every year for three years, your revenue is lowered by 56%.

If your portfolio underperformed by 56%, I’m guessing you’d be looking for a new investment adviser.  Likewise, if your revenue is 56% below where it should be, I’m wondering if your CFO isn’t thinking about a new CMO.

I’ve been fortunate to work with many companies who understand the financial leverage keeping customers holds for your company.  And I’ve helped a few gain insight into this leverage.

Which leads me to ask:

– Are you investing appropriately in keeping those customers?
– Does your company know how many customers it’s losing?

Tell us how you’re getting it right (or wish you were) in the comments.

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Getting It Just Right: Measuring Customer Success

In an earlier post, I discussed how to get measuring customer success right.  It sparked quite a few questions about how to choose the measurement and how to ensure it causes you to be aligned with your customer’s business success.  Here are some thoughts about how to get it just right.

The Goldilocks Customer Success Metric

In my earlier post, I compared two public safety companies that had very Measuring Customer Successdifferent measurements of how their customers became successful because of their products.

One was RedFlex, whose most often cited metric was the number of red light tickets issued because of their cameras (though, I don’t think they want to be measured this way).  This metric misses the mark, because it does not measure an outcome that is of value to the people who have to make a decision on the purchase of the camera system.  The goal is public safety, not more tickets.

In contrast, ShotSpotter (SST) measured a variety of outcomes, including number of arrests resulting from gunshots detected and number of convictions made easier because of their data.  The goal—public safety—is the same, but the metrics are directly relevant to the outcome.

Let’s analyze these:

Neither company chose what I’ll call the “papa bear” metric, which is something such as increased public safety.  This metric is far too broad, far too hard to measure, and while both companies do something that affects public safety, neither can claim to have increased it directly.

The number of tickets metric, which I’ll call the “mama bear” metric, is too narrow.  It measures the direct result of the system, but it does not take into account any of the results the activity produces.

The number of arrests metric is the Goldilocks metric (or one of them).  It’s not the direct result of the system (you could measure number of gunshots identified), and it does not claim to be a panacea for all police issues.  It does measure an outcome most of us can link directly to which is increased public safety (criminals get arrested), and one the immediate buyer (police department) and the ultimate buyer (political leadership) can relate to and definitely care about.

One alternative to the number of tickets metric might be to look at the total number of accidents at intersections with red light cameras.  For most of us, fewer accidents mean safer streets.

So How Do You Choose Your Customer Success Metric?

Let’s assume for the moment you are selling to a business.

Papa Bear 

Increase revenue or reduce costs.  I hope whatever it is you are selling to the business does one or both of these, or I suspect your prospective customer will never buy.  That said, with very few exceptions, your product or service probably does not directly do either one, and the outcomes of your product are not “more revenue.”  They should do things that lead to one of these two.

These are the wrong metrics.

Mama Bear 

More twitter followers (sorry, social media folks, this isn’t a business outcome).  This is certainly a metric, but for most businesses, it doesn’t produce something effective, nor does it (in any meaningful way) affect costs or revenue.  It’s too narrow, and too immediate. Other examples are things such as, “keeps all your customer activity in one place” or “ensures everyone knows the correct procedures.”

Those might be things your product does, but they are not why your customer buys.

The Goldilocks Metric (encore) 

If you were selling a product to a marketing department, the outcome might be “produces more leads in the pipeline” or “shortens the time to conversion to a sale.”  Both of those are things your product might do where you can measure the effect your product has on either number of leads or time to conversion, and the metric has a credible effect on the business (in these examples, more revenue).

In another recent post, I discussed Christensen’s idea of “hiring” a product to “do a job.” Your customer has a job they need done (e.g., they need more leads).  That’s something they hire a product to do.  And it’s something you can measure before and after they buy your product, so you and they can tell how effective your product is for them.

Another way to consider this is that every team, every group, and every department in a company has business objectives they can measure.  Your product needs to help their measurement of at least one of those business objectives moving in the right direction.

The Goldilocks metric has to be specific and countable.   ShotSpotter counts the number of prosecutions and convictions that use their data.  You can count number of leads, length of sales cycle, reduction in overhead, etc.

So finding the right metric is really simple:   It is a business objective, and it is countable.

Get that right, and you’ll have no trouble getting your customers to show you just how successful you are for them.  Which is just right.

Tell us how you are measuring your customers’ success in the comments.

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