Marketers have come a long way in partnering with enterprise technology organizations to collect, analyze, and use information across many important applications. Much of this is driven by optimization aspirations, and, indeed, there's been much improvement. We know what customers are buying, and what they're not buying. But we don't know much about their pre-purchase browsing, product comparison, and ultimate selection process.
If it were possible to learn about what products customers looked at, what features interested them, and what parameters were important in their decision-making process, we would know a great deal more about which products to offer, how to market and merchandise them to improve conversion, and how to build customer experiences that resonate with the buyers' wants and needs.
When online, consumers leave a trail of bread crumbs that lead channels and manufacturers to better insights into the purchase process, product relevancy, and interest levels. Analytics of these clicks have led to a better understanding of correlations between online tools (such as product-feature explanations, product videos, or customer reviews) and online purchases. But most businesses operate in a multichannel world where e-commerce is not the primary or sole customer interaction, which means online analytics are insufficient.
Offline pre-purchase behavior data is essential in understanding what buyers are looking for, and what in-person experiential marketing and merchandising tactics will best inform and satisfy these decision-makers. Whether at a tradeshow, in a store, or at other offline venues, more focus and attention must be paid to capturing data that exposes customer behavior -- which products they looked at, which features they spent time examining, what problems they are trying to solve.
Studies have shown that in the absence of comprehensible information, customers determine their own baseline decision criteria for comparing products. Whereas a manufacturer may have designed a product to include features relating to performance, for example, a customer may overlook these features and focus on form factor, or price -- unless these features, advantages, and benefits are exposed to the customer in an articulate and effective manner. Without knowledge into whether a customer was educated about these performance features, and whether she considered them, in the event that a competitor's product is selected, marketers may be misled into thinking that those performance advantages are not worth the cost. What would be valuable is a quantitative understanding of whether the customer knew about features and still chose another product. Of course, if that is the case, then the conclusion described earlier may be correct. However, if the customer was not aware of these features, and selected another product, then there is no conclusive insight as to the real-market value of the features, begging the question: Would the customer have chosen this product had she known of these specific features?
This is but one example of why it's important not only to find ways to effectively communicate product features, advantages, and benefits, but also to document and measure whether the customer experienced them. This information can then be connected with next-step behavior.
Product marketers making assumptions about customer needs and decisions can lead to great risks (and financial consequences). When data is available to lend insight into how customers make purchasing decisions, those risks can be reduced or eliminated. By understanding which products, features, or key value propositions resonated with customers during their decision process, manufacturers and their sales channels can leverage the insight within marketing tactics and better respond to consumer demands. Returns on the investment in technology and time to better capture and analyze data are significant. Many marketers are unaware that these capabilities are now available. Through the use of interactive product experiences at a variety of offline venues, customers can learn about products while manufacturers and sales channels can capture customer behavior data. These digital environments have the dual advantages of improving the customer experience while also providing the means to gain insight into real customer needs.
The purchase decision is a critical milestone for everyone involved in the sales process. But learning about pre-purchase behavior is equally important. Answering the question "Why did the customer buy this product?" will eliminate guesswork, and will lead to long-term successful customer relationships.
About the Author
Gavin Finn is president and CEO of Massachusetts-based Kaon Interactive (www.kaon.com), creators of visually compelling, 3-D interactive sales and marketing solutions that empower individuals to interact with your products. The dynamic virtual "experiences" can be leveraged at trade shows and remote sales venues, on Web sites and laptops, and within PDFs.
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