The growing availability of behavioral data, sophistication of measurement tools, and increase in opportunities to provide targeted content are all contributing to significant growth in behavioral targeting programs. In less than 30 seconds, you can create Facebook ads segmented to a specific city, gender, and even relationship status. All of a sudden, marketers are scrambling to deliver even more customized content, across multiple screens, to an increasingly sophisticated audience.
When it works, it can be an incredibly effective tool. But, at times, these educated guesses about what a user will respond to fail. Miserably. The ridiculous “you may be interested in” suggestions. The “related items” that have zero relation to your search. The ad promoting bargain linens when you are looking for 600-thread count Egyptian cotton sheets.
As the pressure on marketing executives to deliver measurable results grows, finding the key to successful behavioral programs is becoming a highly visible priority. Several factors can contribute to behavioral programs that miss the mark:
What do you really know about the criteria used by third-party providers and business partners driving traffic your way? How stringent are they in validating list criteria and interaction points? Are their definitions the same as yours? Visibility into external data has historically been a major challenge for behavioral marketers. Selling data to a wide variety of customers means that many data providers use the lowest common denominator of criteria. For example, a regional bank and a global financial site may both be considered “financial” indicators – even though they operate in fundamentally different markets. As competition among external data providers continues to increase, businesses have enhanced opportunities to require better validated data – and data better-customized to their business.
How much is enough? What is too much? Do you really have 16 different personas types – even if there are only five fundamental services your business delivers? Just because the data may be available to hyper-segment your users, the return may not be there. Segment users too finely and risk incorrect categorization. Cast too large a net and the message may not be specific enough to convert. Consider the amount of truly unique offers, messages, and content and align your segments to them. If the categories are not fundamentally unique in message or call to action, it may be more effective to consolidate. If few natural segments rise to the top, consider A/B testing several messages to a larger group to draw out potential segmentation points.
How different are the metrics and objectives across the business? If one group is targeted with lead generation, their approach to qualification may be fundamentally different than a group whose metric is sales conversion. The result – an internal battle between volume and quality of leads. While this is a long-standing challenge for almost all businesses, the impact multiplies with technology and targeting. Effective behavioral programs require alignment across the customer experience – both customer-facing and internal touchpoints. While often complicated, both politically and technically – gaining alignment on core metrics and definitions is critical to the long-term success of the program.
Even the best designed, customized user experience may fail if the fundamentals are not solid. The message may not be that unique. The product may not be that compelling. The price is not competitive. Set reasonable expectations and realize that even if the message finds the right audience, the end offer must stand on its own.