Data-driven marketing has reached critical mass. Suffice it to say, data has become one of the most valuable, if not the most valuable asset a business can obtain. Almost everything customers do can be tracked, anonymized, and shared with “the cloud” for advertisers to see and use. Data-driven marketing is transforming the agency landscape as well, as more and more agencies are developing and integrating data-driven capabilities. This is because data-driven marketing definitively drives incremental business for marketers, as many published case studies have proven.
However, while marketers have clearly embraced the value of data, most have no idea that the data they are now using is exactly the same as the data their direct competitors are using. The risk is that most data-driven strategies are easily and readily replicated by other advertisers in a category. It happens without intention mostly because the same data is being made available to all marketers.
To illustrate this, consider a planning exercise for an energy company. The agency was instructed to use specific audience segments on energy consumers in the media planning. Upon further investigation, it was revealed that these segments were built by one of the largest data brokers in the world. These same segments are widely available in the “open marketplace” of data for any of the energy company’s competitors to use at their discretion. Every energy company has the same access and opportunity to use that data in their marketing efforts.
This example should concern marketers about the reliance on 3rd party data, defined as data collected and sold by a data aggregator and broker. A marketer’s own transactional, customer data (1st party) may be just as undifferentiated. Why? Not because of data security issues, but because of the general nature of consumer behavior in a given category. No brand maintains 100% brand loyalty among their customer base. On the contrary, many of a brand’s customers are also many other brands’ customers within the very same category. Therefore, it is very likely that any marketer collecting transactional data has roughly the same data as their competitors.
Transactional 1st party data and 3rd party data should be viewed as table stakes. Marketers need to focus on creating differentiation in their own data, in as many meaningful ways as possible. Anything short of this would be the equivalent of running in place.
This needed differentiation can stem from the establishment of unique, interactive consumer experiences with the brand. The interaction is critical in enabling data acquisition. Three areas to achieve differentiated experiences are noted below:
- Create differentiated content for your brand. Then use content consumption as an additive means to segment your customers and prospects. Note that it must be differentiated content, something not offered by your competitive set. For example, content about the different types of life insurance coming from a life insurance company would yield little if any differentiation. It is important to your customer/prospect user experience, but it is table stakes in that category. Think beyond your category to leverage content areas that can be unique for your brand.
- Create a differentiated service around your brand. Tracking service interactions, patterns, and preferences will also help you segment customers and prospects. Dollar Shave Club and Warby Parker are examples of service differentiation that stand out in their categories. They know much more about their audience because of their service layer, which helps them communicate more meaningfully and relevantly.
- Create a differentiated relationship with your brand. Conversation can be a meaningful differentiator. Companies that use social media and create deeply interactive relationships with individual customers and prospects can code those interactions as data points. Those relationships can become part of the marketing process that allows brands to create more meaningful differentiation, respond more quickly to trends, and react more quickly to threats and opportunities.
Jack Welch, famed GE CEO, operated under the belief that there are two sources of competitive advantage. First, to learn more about your customers faster than the competition. Second, to turn what you learn about your customers into action faster than the competition.
The starting point for learning and informing future action is a mechanism for obtaining proprietary data, critical to differentiating a brand from the competitive set.