Remember when data-driven marketing was an emerging, innovative approach? Today, all business decisions have become more data-driven, giving rise to an overabundance of data offerings—some more useful than others. This has created confusion and data fatigue amongst brands, making it difficult to answer the question, “how can I ensure my data strategy moves the needle?”
Addressing this question requires you to look at all the information you have access to and determine ways to make it more useful for marketing.
First-party data in a customer relationship management system (CRM) is arguably the most valuable asset a marketer can have. But, many companies, even ones with robust CRMs, have a blind spot once customers leave their store. Having a whole-wallet view of customer behavior—that is, an understanding of where else their customers shopped—is imperative to truly understanding customers and growing market share.
For example, one of our clients, a popular apparel company, believed that 20% of their customers were loyal, based on what they saw in their CRM data. However, once they looked through the whole-wallet lens, only 5% were true brand loyalists, while the rest were actually just heavy category shoppers, with many shopping primarily at direct competitors. This insight changed the way they identified headroom and engaged current and future customers.
While demographic data can be used as the foundation on which to build a data-driven marketing strategy, there are challenges in using that data set on it’s own. Chiefly, that it casts a wide, nondescript net based on rudimentary data points, like gender and age, which do not accurately reflect the type of brands a consumer is actually interested in. And, with new shopper influencer sets emerging, like “Perennials,” which span generations, demographic data is becoming the lowest rung of the data set totem pole.
Consider this scenario: Three women ages 30-35. One is married with two young children. One is single and likes to work out every day. And, the last one travels regularly. Just looking at demographic data, a sporting goods company may waste marketing dollars trying to get in front of all three of these women. But, by looking at actual purchase behavior, the company can target their marketing dollars more effectively to the women who have the highest propensity to buy their brand.
From its start, digital has been one of marketing’s most accountable forms of media. But, as digital media surpasses traditional forms, the need to tie this increased spend to real business outcomes is increasingly important. It’s easy to measure online conversions, but given that the majority of purchases still take place in a store, proxies such as click-through rate (CTR) are becoming less acceptable for smart, data-driven companies who want to prove the actual downstream value of their marketing programs.
That’s not to say that CTRs should be thrown out. This data just needs to be enriched with purchase data to connect digital ad exposure to actual in-store and online sales. By using data to close the loop on their marketing spend, companies can confidently show correlation between campaigns and improved sales and market share captured from competitors.
Three questions to ask potential data providers
Not all data is created equal, and today’s marketers should ask themselves three key questions when evaluating the data and analytics support they need for their marketing efforts:
- Does it help me better understand customer behavior?
- Is the scale significant enough to move the needle on my business?
- Do I have reliable partners to work with who have clear rights to their data? (This is especially important given upcoming GDPR changes.)
The use of data and analytics in marketing is critical in helping brands learn more about customers and prospects. The three questions above will help brands engage with more of the right data providers, comply with privacy laws, shape effective data-driven marketing strategies, and realize greater marketing ROI.