Five Actionable Lessons Learned from Predictive Customer Journey Analytics

I’ve been actively researching customer behavior in the financial and retail industries for over 30 years now, and what fascinates me the most is determining the leading indicators of future customer choices and interactions. At Corios we call this predictive customer journey analysis.

journey noun_81349The most important and most elusive part of being responsive to customer journeys is identifying leading indicators. Leading indicators will tell you what each customer is likely to need or want, in advance of the customer making a decision, in a way that gives the firm enough time to prepare and respond with a relevant solution.

Predicting future customer activity is more important than merely observing past activity. If used correctly, history can be a wonderful predictor of future choices. However too often, marketing recommendations are based on customer averages, rather than on trends or events. The customer average is a good predictor if we have no other information, but in this era, we have much more information available to help predict the customer’s next actions. Being aware of, and utilizing this information effectively, is vital.  Often firms have one shot at delivering a relevant solution within a finite window of opportunity. Once that window closes, another opportunity may not present itself for days, months or years.

To underline the importance of effectively tackling the challenge of predictive customer journeys, I’ve researched the actions of our Corios clients, and catalogued the five practices that lead to the biggest differences between successful and less-than-successful efforts.

 

1) Set predictable goals, and monitor progress towards achieving them

Do you remember the era of web server logs and vendors like WebTrends? Amazingly, they are still in business, a few blocks away from Corios HQ in downtown Portland. When their software first emerged, it was a very solid way of reporting web server statistics: pages, hits and errors (the reports always reminded me of baseball scores.) However, what has always been missing from these reports was any indication of whether the firm using the web server was actually making any money from customers. A problem that is still relevant now. Business owners receive too many reports providing historical perspectives on activity, rather than whether these activities moved the needle by delivering meaningful value to their customers.

Today, these activity reports take the form of interactions across channels, hopefully integrated to the customer level, but the problem still remains that none of these reports inform decision-makers as to whether key objectives are being met, improved, or diluted, as the result of said activity.

Which brings me to my first “difference-making” action when considering customer journey analysis: Can the firm’s decision-makers trace a direct line from interactions to value-producing objectives? The path between interaction and valuable objective should go straight through an applied analytic model that identifies which interactions produce value, such as incremental closed sales or increased value per sale, as opposed to being completely irrelevant.

When this line of sight between activity and outcome is clear, unambiguous, and a leading indicator, decision-makers can redirect resources toward stimulating the most value-producing interactions with customers.

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What does predictive customer journey analytics look like?

Walking through a predictive customer journey dashboard and results

When will a customer take action? How rapidly will they respond to a bank offer for credit, or to a retailer’s offer for a sales promotion? If you don’t know the answers to these questions, you can’t really develop a sound strategy for delivering the right offer to the right customer at the right time. This is what predictive customer journey analytics are all about.

Many of our clients are visual thinkers, so we wanted to provide everyone a visual walkthrough of what predictive customer journey analytics looks like to a business decision maker. We built an illustration and published a narrated video of Corios Veloce at work, using results from a recent engagement as our inspiration. It’s a short, 10-minute exploration of the new insights decision makers can use to determine when to engage with a customer at the best time, using leading indicators from transaction and interaction data.

 

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Customer behavior is neither simple nor linear

Especially determining the onset of changing customer behavior

When will a customer take action? How rapidly will they respond to a bank offer for credit, or to a retailer’s offer for a sales promotion? If you don’t know the answers to these questions, you can’t really develop a sound strategy for delivering the right offer to the right customer at the right time.

As you might already know, at Corios, we tell the story numbers can’t. Telling the story of the consumers, using their transactions as the ink on the page, meant developing an entirely new way of analyzing data, and it stems from looking at consumer behavior differently than the traditional conventions of applied mathematics and big data.

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Let’s Advance

If you’re not advancing, you’re retreating.

At Corios, one of our core values is “Sharpen the Saw.” This means that we believe in a constant pursuit of knowledge and excellence – and that our team never rests on our laurels or passes up an opportunity to grow and improve.

Corios Advance

To that end, we’re excited to report that we just wrapped up our annual company event in the wild. While some other companies might refer to this outing as a “retreat,” we decided to do something a little bit different.

Rather than taking a retreat – or step back – we sought to get everyone together to talk about how we can advance our work. The new name for our event, the Advance, reflects this aim of advancing our team bonds, our company strategies, and our ideas about what makes Corios great!

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Corios Team Story: Meet Austin Barber

At Corios, we know that our talented team members are the fuel that propel our organization and the cornerstone to our success – so who better to tell the Corios story? Get to know more about the people behind the numbers in our new segment, “Team Stories.”

 

It’s not often that a management analytics firm is compared to a sports team – but for Analytics Consultant Austin Barber, Corios shares some of the same attributes. Since joining our firm in 2015, Austin has enjoyed not only this team spirit – but also the challenging work, mentorship, and vibrant environment at Corios.

“I have an athletic background, so I’ve learned to seek out a team environment,” says Austin. “I really appreciate being a part of a cohesive team. Everyone on the Corios team thrives together: whether we’re in the weeds working on a challenging problem for a client, or seeing the fruits of our labor and celebrating together – that’s a big area of support for me.”
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