Looking across geographies and industries, it’s striking to note the profound differences between how companies optimize the sizing and allocation of their marketing resources. In this first part of a two-part series, I’ll draw from the best and worst practices in organizations of all sizes and share some practical advice for how you can improve your marketing.
1. Break Down Organizational Silos
Typical barriers to optimizing marketing spend spring out of the separation of functional responsibility and siloed analytical tools for assessing advertising versus CRM activities. What’s needed is an integrated approach for combining all customer communications into a single evaluation model. KLM/Air France is a good example of a company that merges its research and analytics functions to combine research-based insights and behavioral data-driven insights. This creates a seamless view of understanding the market, consumer motivations and acquisition as well as experience, retention and loyalty analytics.
2. Embrace All Data
While a Google search for “big data” and “marketing mix modeling” yields little commonality, and on Wikipedia, they seem to live in separate silos, the biggest turbo-charger of marketing optimization modeling is the wealth of new data that can be included in these analyses. Many companies are now taking what was originally “engineering data” and re-purposing it for marketing optimization. For example, some telcos are looking at calling pattern data and data usage, etc. Big Data is going to transform marketing decision-making, but what we mean by data can come from non-traditional, non-marketing, sources.
3. Combine Techniques
Marketing mix modeling traditionally uses aggregate data inputs like TV GRPs or print spend to try to explain aggregate outputs like total sales. But now what we see are increasingly granular inputs and outputs being included in marketing mix modeling. Why not combine aggregate marketing mix modeling with disaggregate customer analytics? The best practice now marries the comprehensiveness of marketing mix data looking at the totality of marketing spend with what were previously seen as CRM techniques looking at disaggregate customer level data for acquisition, retention, up-sell, ARPU, customer lifetime models and so on.
4. Use Multiple Lenses
A multi-lens approach creates the greatest analytical power. For example, retailers often look to analytics for guidance on how to identify private label opportunities, or to rank strongly performing vs weakly performing SKUs. An effective multi-lens analysis for this will combine Price/SKU/Promo/Cannibalization type merchandizing analysis (ie: meta data about SKU margins, sales velocities, cannibalization, etc.) with customer analytics (ie: individual customer data showing SKUs association with high value customers) and basket analysis (ie: till or transaction data for each “basket” that shows SKUs association with high value baskets).
5. Build Models That Look at Brand and Retention Activities Together
At many companies, separate silos work on analyzing brand activities (like TV or online) and addressing CRM plans (like email, or direct mail) when they should analyze spend holistically across different silos. Another common mistake is using the wrong metric. Net adds or numbers of members is a terrible measure of business performance. While results can be improved by either greater acquisition or reduced retention, each is achieved with very different marketing tactics and has fundamentally different business implications.
One example from a company that gets this right: A global white goods company whose marketing program was once entirely dominated by television advertising. Today, their customers spend more time online than watching TV. The company recognizes that the role of MarCom is relevant to each step of the customer life cycle. When the shopper is in the discovery stage researching their new refrigerator, word-of-mouth creates reach. During the buying phase, blogs and communities offer an extra depth of engagement. And post-purchase, social media and CRM tools like email continue to engage to enhance the post-purchase experience.
While these optimization steps might not happen overnight, marketing affords many opportunities for performance improvement by aggregating small wins. Next time, I’ll provide five more tips to improve your marketing program.