Marketing automation typically focuses on driving sales, mainly using past purchases or late funnel behavior (e.g., paid search) as a predictor of an upcoming purchase. While effective in increasing sales, this widely implemented strategy can misuse the brands and industries that adopt it, as it encourages perpetual devaluation of products or services.
Narrowing a brand’s focus solely on the issues associated with the transformation risks snatching away the customer experience of the key ingredients that underlie long-term success. We live in a data-rich world and insights are becoming more vibrant every day. With this in mind, companies and advertisers can strategically weave together all the data collected during the customer experience.
This enables them to understand every assumption available during the customer interaction and to learn what benefits the customer the most at a given time. But by focusing exclusively on information collected from customers, brands risk falling under the law of return reduction. Even companies with meaningful consumer interactions or rich service offer to strive to gain influential relevant insights.
Only by using a larger dataset can we understand how people become customers in the first place, are less likely to buy again, and how societal developments affect the growth or struggle of a brand. Here we look at how we can get a more complete picture of current and future customers.
Over the past several years, almost every industry has come close to the “Holy Grail” of real-time, direct, and personalized engagement, capitalizing on opportunity-oriented marketing gifts.
Nonetheless, the growing toolset encourages brands to ultimately focus on funnel initiatives, which actually affect the longevity of the business: the relationship. While the information on past purchases or late-funnel behavior provides value and is effective in identifying habitual changes or actual needs, it does not provide a comparative surface level and insights into consumers ’future behavior or leads them to a specific purchase first.
By incorporating AI, brands can successfully engage with their audience in a more holistic, supportive, and practical way. Not only the content of the language (e.g., keywords) but also the technology of understanding its meaning opens up the possibility of better guessing the interests and motives of the consumers. Instead, brands can tune consumer interactions for satisfaction and enjoyment and ultimately gain strong insights for future use.
