Big consumer data: the good, the bad, and the ugly

Big data, customer relationship management, customer analytics, and other similar terms are hot topics right now, with companies investing substantial time and funds to try and use their customer data to improve their performance. Yet most companies report poor returns from these efforts and struggle to make them work. In his talk, Mike leveraged his experience using customer analytics to address this opportunity and discuss common pitfalls, good practice, and other tips for getting the most from your customer data.

Mike began by sharing a few good examples (Tesco in the UK, location data testing in Australia), counterbalanced by some too-often bad examples (airline and hotel retargeting, LinkedIn suggesting an MBA information session to a Harvard MBA) and some really awful examples (Facebook selling him bras!). He reminded the audience that the objective of leveraging customer knowledge to achieve higher customer satisfaction and profitability is not new; rather the challenge is to scale from individual actions (Peg’s Diner) to thousands or millions of customers.

He then shared three thoughts on how to deliver better results.

First, he quoted Ted Levitt and Jerry McGuire to highlight the need to focus on output, not tools and financial impact (“Show me the money!”), not activity. He then shared his concept of BS (business significance), which assesses client uncertainty and value at risk as a helpful way to identify opportunities.

His second point was that understanding how analytical techniques work is critical. That includes:

  • correct usage of basics like averages, which are often misused to create meaningless numbers;
  • remembering that correlation is not causality; and
  • challenging whether the metrics being used are aligned with the business purpose of the analysis.

Finally, he suggested that creativity was a missing element in many big data efforts. This is especially true when creating sufficiently tailored offers for analysts to target, as it is futile to target undifferentiated offers or communications. He also posited that qualitative research has a major role to play to go beyond behavioural data and understand why consumers act as they do. He ended with a plea for clearer, more concise communications, suggesting that often the insight was obscured by dense charting and verboseness.

 Mike recently published his first (and last) book, 52 Things We Wish Someone Had Told Us About Customer Analytics, co-authored with his son Alex. The book captures real-life lessons they learned over their careers, with a focus on practical applications of analytics that connect methodologies and processes to create impactful outcomes.