AI and Analytics for Business
Speedbumps or Dead Ends? Latest Thoughts on Obstacles to Achieving Customer Centricity.
One of the highlights of my work with AIAB is bringing companies together to speak candidly about their experiences implementing customer analytics and managing talent development to sustain momentum. AIAB’s major research projects often take the limelight, but I equally enjoy the intimate, cross-industry settings we can carve out to hear the latest and greatest from practitioners. In late June, Teradata, a AIAB corporate sponsor, helped us bring that conversation to an outstanding forum of more than 35 experienced marketing and analytics executives from leading companies across industries (Amgen, Electronic Arts, Roche, GAP, Pintrest, Salesforce, and Wells Fargo to name a few).
The topic was ostensibly ‘Establishing Competitive Advantage through Customer Centricity,’ with the aim of clarifying this important concept and how it impacts performance metrics, organizational structures, salesforce incentives, and more—but this does little justice to how participants actually shaped the agenda. I’ve spoken on customer centricity at many large conferences, but I always prefer the small venues where participants feel less inhibited asking questions, sharing experiences (both good and bad), and challenging different aspects of customer centricity as we walk through them.
Barriers to Adopting Customer Centricity
As someone deeply interested in bringing customer value to life, I find pushback from practitioners—and their dialogue with each other on shared experiences—to offer the most valuable insight into the barriers facing firms as they strive to achieve customer centricity. And in these smaller settings, the key themes that grab the group’s interest always vary. Here’s a quick rundown of key topics from the recent session that’s got me thinking:
Customer profits are harder to track than costs. A critical component of moving firms toward customer centricity is rethinking performance metrics, from company valuation to salesforce incentives. One participant noted that the latter is complicated by the fact that customer profitability is harder to track than costs, especially at a granular level. This is a fair point and one that I’m hearing more often. In addition to valuation metrics (Customer Lifetime Value (CLV) alongside 10-K, 10-Q, and others), we need to develop customer-centric accounting standards. Until we figure that part out, it may be harder for some firms to get a truly customer-centric sales/CRM system off the ground. This is an area I intend to discuss and research further with AIAB’s partner companies.
Branding is powerful, but it’s difficult to quantify. This sparked a particularly lively debate. I noted that I’m much more interested in customer acquisition, retention, and development than branding for “what moves the needle.” I was called out for this immediately with examples of strong brands and the resulting benefits. I should clarify that it’s not that branding has no impact, it’s just incredibly difficult to manage and measure. This is a reality we as marketers face.
Conversely, I strongly believe you can value the customer base. In a crude example, you could calculate CLV for each customer, add it up, subtract operating costs, and you have the value of the firm! I’m also a data jockey, so I don’t come without biases regarding branding. But when we think about restructuring entire businesses around customer centricity, not just the marketing departments, I can’t help but gravitate to the more quantifiable, data-driven metrics that CFOs, CEOs, and others will sit up and take notice. Having said that, I can’t deny how brands can create stickiness for customers and it’s certainly an area that warrants further research to quantify.
Privacy. As we think about customer centricity and calculating CLV, concerns for privacy increasingly crop up, and the recent session was no exception. I think this stems from thinking that if we want to be increasingly customer centric, we need to know more and more about our customers– and no firm wants to place creepy data collection at the center of its business model.
The good news is that you don’t need creepy data to be customer centric. I would take RFM (Recency Frequency, Monetary Value) over invasive personal data any day—and that metric was around well before the digital marketing boom. Most of the appealing measures that are enabled by emerging technologies (e.g., social media, geolocation, browsing activities) aren’t nearly as predictive as we may think, and certainly not to the level of RFM. I’d hate for firms to stall their pivot toward customer centricity—or worse, for customers to feel their privacy violated—all because companies believe they need extensive (read “excessive”) data gathering to move forward.
Customer Centricity: From Concept to Implementation
As I reminded everyone at our recent event, none of these ideas are set in stone, and while there are some great case studies in customer centricity, we’ve not arrived at a textbook consensus. But the dialogue is certainly evolving. A few years ago, it was the very concepts embedded in customer centricity that attracted the most attention, but now there’s plenty of books in circulation (one that’s particularly great)—and now it’s more about the barriers to achieving a truly customer centric organization. I will continue my roadshows and hear more from practitioners, but I’d like to thank those at our recent session, with a special thanks to Teradata for helping us bring everyone together.
And if you have any research, case studies, or experiences that confirm or refute any of the above topics, by all means send my way (email@example.com).