As Summer 2021 speeds along, I find myself wondering aloud:
“Is the worst really behind us?”
“Will Lollapalooza actually happen this year?”
And of course – “What consumer behaviors adopted in the last year will stick around?”
A recent conversation with my local colleagues named Foxtrot Market the Chicago pandemic MVP, a brand that earned consumer loyalty through excellent product selection and speedy delivery. That loyalty shows no signs of waning.
Marketers are asking some of the same questions (the one about consumer behavior at least). If last year was about survival via accelerated digital transformation, this year is about retaining those newfound customers. Given that consumers seem to be generally quite happy with the new brands and shopping behaviors they adapted to in the last year, that digital acceleration was not for naught. Now, the competition to win customers’ habits and hearts for good is as hot as the sand on Oak Street beach.
Marketers in pursuit of better, more relevant customer experiences to beat out the competition are investing in personalization engines, wooed by the promise of improved conversion rates if we can put the right recommendation in front of the right customer at the right time. But, executing those goals proves challenging, and despite their promise, personalization engines are one of the most underutilized investments in the martech stack. Barriers to adoption and execution abound, but this year’s Magic Quadrant for Personalization Engines (subscription required) reveals that vendors are responding by offering industry-specific templates, models, and reporting to ensure that marketers can easily identify the right personalization tactic to execute, and measure the result with the most category-relevant KPIs.
Marketing teams who have mastered product recommendations might next look to site search as a means to stay ahead of the competition, as personalization vendors increasingly support smarter search experiences. This year’s Magic Quadrant evaluation saw improved natural language processing capabilities to better match results to customer intent. We also saw more use of AI to comb through inventory without being limited to details contained in product descriptions, making it easier for the customer to find their perfect pair of summer cutoffs.
For more on how consumer behavior is changing and how personalization engines can help create better shopping experiences, make sure your summer reading list includes How Retail Marketers Can Prepare for Long-Term Pandemic Impacts on Consumer Shopping Behavior and Critical Capabilities for Personalization Engines (subscription required).