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Customer Analytics

The Customer Insights’ Imperative for CMOs

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“The most critical capability of the CMO is to have a profound, deep understanding of customers and their needs and know how to engage and serve them.  This of course involves knowledge of data and analytics. – Jamie Moldafsky, CMO, Wells Fargo, in “Redefining the CMO,” Deloitte Review, issue 22.

According to a recent study by the CMO Council and Deloitte, “CMOs have been increasingly asked to elevate their activities from brand and marketing plan management to acting as an enterprise-wide revenue driver that taps into the hearts and minds of their customers.”  Based on this research, Deloitte makes three recommendations on where CMOs should start.  One of these recommendations is to “relentlessly pursue customer expertise.”

The imperative is clear: today’s CMO is no longer just the brand steward, but also the customer steward.  He or she should be able to steer marketing strategies and activities that, as the report mentions, “engage customers with messaging that better speaks to their needs and values, establishing an ongoing relationship rather than a transactional one.”

The question then, is how the CMO becomes the customer steward.  Part of the equation involves traditional marketing tools and techniques such as personas, NPS, and focus groups in order to fully understand the customer (or customers) and how to meet their needs.  The other part – as mentioned by Moldafsky in her quote – is having a knowledge of data and analytics.  Today’s CMO must be able to analyze meaningful customer data in order to “lead the customer-centric charge.”

Unfortunately for many CMOs that presents a technical challenge, and for some, one that simply does not fit within their marketing budget.  The technical challenge is how to build an enterprise-class customer analytics platform that enables you to ask vital questions of your data.  And yes, it’s almost always build – even if you buy a software package, most require a significant amount of customization and development in order to make it integrate with your existing systems, deliver the answers to your business questions, and is user-friendly.  On top of that, you may also need a data scientist to build out the questions and structure the data so that those questions can be easily answered.  All of this takes time – many months – and money.  Lots of money.

You might be a CMO with a fairly unlimited technology budget. But chances are you do not have unlimited time. The average CMO has a tenure of just 4.1 years, which is half the average tenure for a CEO, and less than that of a CFO, CIO, or CHRO.

How do you, the ambitious CMO who understands the opportunity to be the customer steward and the challenges presented with a traditional approach to a customer analytics platform, resolve this inherent conflict?  The answer is simple: you seek out technology that is built for marketers, but robust enough to deliver the insights you need. One that works with your data, but that does not involve months of development efforts.

This approach puts you on the path spelled out in the Deloitte report: “CMOs wishing to transform their role can take advantage of their unique position to elevate themselves as the customer expert with stakeholders across the enterprise.”

Read more blog posts on customer insights and analyzing customer data:

Pull a Rabbit out of your Hat – or at Least Pull Insight from Your Data

Revelwood Named IBM Customer Analytics Partner of the Year

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Online Retailers: Don’t Lose Out on Impulse Purchases

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Impulse purchasing accounts for a lot of revenue. According to a survey by CreditCards.com:

  • 5 in 6 Americans say they have made impulse buys
  • 84% of poll respondents say they’ve made an impulse purchase at some time
  • 1/3 of consumers who make more than $75K a year have made an impulse purchase of $1,000 or more.

Traditional retailers employ a number of strategies to generate impulse purchases. These include a transaction building strategy, where the retailer strategically places complementary products next to each other; need recognition, where you display products relevant to a target market’s needs and interests; and cross-merchandising, where a retailer suggests products that work well together.

But capturing impulse purchases is largely the domain of brick and mortar stores. The same study shows that nearly 8 in 10 impulse purchases are made in a physical store. The challenge facing today’s online retailers is how they can increase impulse purchasing when customers shop on their sites.

Amazon has mastered the art of deploying some of these strategies – particularly serving up complementary products, displaying products that target a customer’s need, and suggesting products that go together. Netflix does this as well, although not in the context of impulse purchases and/or increasing the customer’s basket. By using customer personalization journeys, Amazon and Netflix have demonstrated how powerful recommendation engines can be.

In the case of Amazon, the retailer (or to more accurately describe the business, the distributor), has developed algorithms based on the items in the customer’s shopping cart, items the customer has rated and liked, and what other customers have viewed and purchased. According to a recent article on MarTechAdvisor, 35% of all Amazon’s sales are “estimated to be generated by the recommendation engine.”

Netflix relies on its recommendation engine to increase viewership and lower customer churn. But custom-built, AI-based recommendation engines do not come cheap. The same article in MarTechAdvisor states “Realizing the importance of having the best recommendation engine, Netflix puts a lot of effort into its algorithm. Updates to the algorithms are researched and tested by a team of over 70 engineers. In 2009, Netflix offered a $1 million prize in an open competition to any research team which could improve on the efficiency of their algorithms.”

Retailers and distributors who do not have the deep pockets to invest in a custom-built, multi-million-dollar development effort might feel they can’t make use of a recommendation engine. Not only is there significant up-front cost, but given the nature of AI, machine learning and predictive analytics, there needs to be an on-going commitment to development efforts. One can’t build a recommendation engine and then let it sit idle. It must be continually improved to leverage the advancements in the field.

But then there’s the potential for increased purchases and capturing those impulse buys. Retailers need to ask themselves not only if that investment in a custom system will pay off (likely it will), but also will it pay off in a timeframe short enough to make a difference for the retailer?

Read more blog posts on customer analytics:

Net Promoter Scores and Customer Outcomes

Using Customer Analytics to Solve Critical Business Challenges

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Net Promoter Score and Customer Outcomes

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We’ve worked with hundreds of companies who primarily measure their customer relationships with one metric: Net Promoter Score (NPS). NPS measures customer experience and predicts business growth by asking one simple question: how likely are you to recommend the company’s product or service? The score is calculated on a 0 – 10 scale based on the response, with those scoring 9 – 10 considered “Promoters,” those scoring 7 – 8 considered “Passives,” and those scoring 0 – 6 considered “Detractors.” The more Promoters you have, the higher your business growth potential is. NPS is seemingly easy to measure and easy for employees throughout the organization to understand.

Marketing and service groups who measure NPS tend to swear by it – and proudly proclaim their 5, 10, or more point increases in NPS that are attributable, loosely, to a new initiative or campaign. Sounds great. So what’s the problem?

Here’s the Problem…

Asking the Right Questions about Customer Outcomes

While Finance is watching the numbers, Marketers are too often focused on moving metrics like NPS, Facebook likes, and Instagram followers that don’t necessarily contribute to the bottom line. You’ve got all this focus on the customer and customer-related activities to move NPS, while NPS doesn’t impact what you think it does.

In fact, research shows that NPS is not correlated with the financial outcomes most organizations care about. According to “Which Customer Metric Best Predicts Financial Performance,” by The American Marketing Association, “Net Promoter Scores are are not backed by any credible evidence of financial predictive ability but have caught on because they seem simple (one item measures it all), prescriptive (you can compute the promoter score for every customer segment) and falsely encouraging (increasing promoter score is believed to increase sales, revenue, share and profits).”

The article goes on to explain that studies show that a higher NPS doesn’t correlate to increased sales, profitability, cash flow, market share, or shareholder value. Instead, customer outcomes such as purchases, attrition, etc., play a huge part in the financial success of an organization. Many marketers are just asking the wrong customer questions.

Asking the Right Questions

What’s the best way to measure and improve customer relationships? There is a better approach to customer measurement. It’s more complicated than a 0-10 scale, but customer relationships can be measured and improved scientifically. We guide our clients towards three major areas of the customer relationship:

  • Retaining the Relationship
    • How do you keep each individual customer’s business?
    • Which customers do you not want to keep?
    • How long have you got with each customer?
  • Growing the Relationship
    • Which customers are likely to buy more (or less)?
    • What is each customer’s next best recommended product or service?
    • How do you sell more, and in a personalized way?
  • Beginning the Relationship
    • Which type of customers do you really want to acquire?
    • How do you attract the right customers?

Attentive readers will note these items are listed in reverse chronological order, and that is intentional. Revelwood recommends starting at the end of the customer relationship and working backward for two reasons:

  • Working backwards through the life cycle is easier due to data availability and complexity
  • This approach yields a faster ROI and is easier to justify internally

Finding the Answers

Financial success won’t come on a ten-point scale. Answering these and many other customer analytics questions is possible and easier than ever before. By leveraging historical data, statistical models, and a bit of know-how, Revelwood helps its clients achieve measurable, justifiable improvements in customer outcomes. Asking and answering the right customer questions will definitively add to the organization’s top and bottom lines. And that’s a score you should promote.

Contacting our Experts

Email info@revelwood.com to set up a discussion to learn more.

References

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Revelwood Named Ingram Micro IBM Analytics Growth Partner of the Year

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Business travel can sometimes be more obligation than enjoyment. There’s always the chance of flight delays and other transportation snafus, long days, and often, the expectation of keeping up with your day job while being out of the office for work. But sometimes there’s that special business trip you look forward to!

That’s how we feel about the annual Ingram ICE event. “ICE” stands for Ingram Cognos Elite and it’s an exclusive program for IBM business partners who demonstrate expertise in selling IBM Cognos solutions. Every year, this event is held in a different location. This year, the ICE event took place in sunny Key Largo, Florida which is always a fun place to have a business trip. To make it even more exciting, this was the second year in a row that Revelwood was named the Ingram Micro IBM Analytics Growth Partner of the Year!

“Revelwood has done an incredible job growing their IBM analytics business through portfolio expansion and new client acquisition,” said David Hino, senior vendor business manager for IBM Software, Ingram Micro. “They are part of an elite group of Ingram Micro and IBM partners that many could learn from.”

Revelwood celebrates earning the Ingram Micro IBM Analytics Growth Partner of the Year award for 2016

From left to right: Vincent Zandvliet, global managing director for IBM/Ingram Partnership, IBM; Scott Zahl, vice president & general manager for Advanced Computing Division, Ingram Micro; Ken Wolf, CEO, Revelwood; Dave Hino, senior vendor business manager for IBM Software, Ingram Micro; Laurie Evans, worldwide channels leader for analytics, IBM.

Our CEO, Ken Wolf, was on-hand to accept the award, but it was earned by the entire Revelwood team. As Ken said in our press release, “Our team earned this award because we have continued to grow our established practice in financial and operational analytics, while also building a successful and award-winning practice in customer analytics and artificial intelligence.” As you can see from the photo, Ken had a great time at the event!

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Revelwood Named IBM Customer Analytics Partner of the Year

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I’m delighted to share that at the recent IBM World of Watson 2016 conference with over 17,000 attendees, Revelwood was named the recipient of IBM’s Worldwide Customer Analytics Business Partner of the Year award. It’s the first time ever that IBM has bestowed this award, and Revelwood was selected among all of IBM’s business partners worldwide who are selling Customer Analytics software and services.

Earning this award was a collective effort between our rapidly-growing Predictive Analytics team and our clients who are embracing the emerging field of Customer Analytics. Two such clients, Southern Farm Bureau Life Insurance and Cardinal Health, were featured speakers at World of Watson, sharing their stories of how Customer Analytics has quickly made a meaningful impact in their efforts to reduce customer churn, increase customer engagement, and enhance the overall customer experience.

Revelwood’s strategy established two years ago was to bring in outside expertise to develop and grow its Customer Analytics practice. We hired our former client, Justin Croft, who was named a 2016 IBM Champion of Analytics to lead the practice, along with Cris Payne, who also brings real-world line of business experience as an expert in the field. Together they have driven our entire team of business and technology experts to become IBM’s most engaged, active, prominent, and successful business partner for Customer Analytics.

And this is just the beginning of our exciting journey towards customer analytics success. Our recently launched product division, Revelwood Labs, is dedicating research and development efforts to pre-packaged solutions for the Customer Analytics market.

I want to thank IBM and our wonderful clients for enabling us to achieve this prestigious award – with special thanks to the tireless work of our amazing Revelwood team!

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