Peter Fader, Professor of Marketing at the Wharton School, puts forth a “data minimization” approach for companies arguing that the histograms you can infer from doing more basic one time analyses, is more cost effective approach to marketing. It’s an interesting argument as it hones in on 1-to-1 marketing’s achilles heel, that of the relative ROI of 1-to-1 compared to the organizational investment required to realize this marketer’s dream. While it’s true that 1-to-1 messaging is difficult and expensive for most companies right now, there is a greater long term disadvantage to “throwing away” historical customer purchase data. True, credit card & billing data are a risk for an organization to house and guard, but this information can safely be stripped without having an impact on order level or purchase history. Also, the cost and complexity of safely storing customer data is coming down greatly. Well thought out data security policies can guard marketing & IT teams from mistakes, as long as the policy is carried out regularly (archive data offsite, secured & detached from external networks).
Think about the danger of not having access to your customer data – what if the histograms that you produced in the early part of the year, prove to be fine for a time, but you’d like to compare the effectiveness of this model against one that your team put forth. You’d have to wait 6+ months to aggregate enough data for the second model to show itself worthy, but not if you’d have simply kept access to the data.
For smaller companies, however, this may be a good option – but only if there’s a high hacking risk and lack of technology support internally. It’s better to reduce risk at that point than to save data for a rainy day – if you don’t have a current plan of using your customer data for marketing activities in the next 6 months, then it will not likely be of use anyway.
