How Technology Helps Predict Consumer Search Behavior – Guide
“Social listening has been very helpful in contextualizing marketing beyond sales data,” says Steve King, founder and CEO of Black Swan Data, in the video above. “Now, we are starting to see patterns that can help us predict consumer behavior 6 to 12 months in advance.” This feature can be useful for product innovators who want to know what consumers will be “concerned, thinking and excited about” in the future. “That’s what Social Prediction can do. It can tell you what products you should create to make sure you take advantage of these new features,” explains King. Advances in AI, machine learning and analytics are helping companies make better predictions with greater accuracy, delivering greater value to advertisers and marketers. Deloitte’s Blab tool, for example, searches over 50,000 sources – including news and social channels – to predict topics and topics that will shape consumer conversations. up 72 hours in advance with 70% accuracy, says Jocelyn Lee, head of the AI advertising practice at creative agency Heat, owned by Deloitte. Armed with this information, CMOs can more efficiently buy programmatic media before identifying trends and developing agile creatives that can be immediately relevant to consumers when the trend kicks in, she says.
The benefits of predictive search
Customer loyalty
As mentioned earlier, customer retention is the number one reason to invest in predictive research. Whether you’re looking for new casino games to play online or coffee makers, you’ll leave if a search engine or website you use doesn’t offer what you’re looking for. It’s a matter of convenience. Nobody wants to spend money looking for something on one site when they can instantly find it on another.
promotion and sales
Autocomplete suggestions in a search bar can also be used to influence customers’ purchasing decisions. Suppose sales of a newly released VR set on your online store are lower than expected. You can make that specific VR set the first suggestion that appears when a customer types “VR set” in the search bar. Of course, this requires serious investment and great work on the part of the tech team, but it is worth it.
Greater customer satisfaction due to customization
Customers love to feel seen and taken care of. This was one of the reasons why Netflix gained unprecedented popularity at the time. Using custom suggestions can (and still is) keep subscriber watch time high. Plus, relevant recommendations tailored to their unique tastes make viewers feel valued. Every online retailer can and should pursue the same thing.
Search engines versus websites
As you’re probably already noticing, Google and online businesses use predictive search differently. According to Google, autocomplete offers “predictions” rather than “suggestions”: “Autocomplete is designed to help people complete an intended search, not to suggest new types of searches.” This is only 90% true, but still. In return, online retailers can do the same, which is likely to increase convenience, satisfaction, and long-term customer retention.
Final note
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