Today's consumer is self-aware and expects some level of personalization in all their online endeavors, and as Marketing Dive reports, 71 percent of consumers like to see personalized ads that speak to their interests and online behavior. Between website cookies, social media activity, search queries, and analytics, brands now have a much easier time contextualizing their website traffic, and these insights lend themselves to behavioral observations that can predict consumers' actions. This information, known as intent data, can be used to flag and target those consumers who seem most likely to make a purchase or conversion. Although intent data isn't a new concept, its availability has exploded in recent years, and marketers have ever-increasing opportunities to leverage it to create more personalized, productive ad campaigns. Here are some tips to build a better personalization strategy.
Create User-Intent Profiles
As Search Engine Land points out, intent data is helping marketers build more relevant, specific user-intent models. One thing that is really spearheading this trend is the growth of voice search and its conversational nature. Regular desktop search might help you learn that "customer A wants to buy dress shoes." With mobile voice search you can get more detailed intent data, like "customer A is seeking sales on black dress shoes, preferably at a location near her Brooklyn neighborhood." Ad personalization can kick in from there, adjusting the type of ad the user sees to account for shoe type, style, color, budget constraints, and nearby store locations.
Use the data that voice search yields to your advantage to build out user-intent profiles, and then let these profiles be a basis to serve more targeted, personalized ads.
Develop Personalized Landing Pages
Once user-intent profiles are in place, you can begin building entire mini-campaigns designed for each profile type. Your landing pages should speak directly to the presumed intent from the particular profile the consumer falls into. So when an online consumer uses the phrase "budget dress shoes at Target," for example, it's clear that they're looking for options to buy—they aren't just browsing or casually mulling over new shoes: The inclusion of "budget" shows that they're trying to find options they can afford, because price is a constraint they can't ignore, and if you're Target—or a Target competitor—you want to show this consumer your great prices on dress shoes.
In this case, your landing page content can speak directly to this type of intent, featuring content that's both price-aware and guides consumers toward budget-friendly shoe options. Through this consistency of tone and focal point, personalized ads can present a seamless front—and analytics can tell you how effectively those consumers are sticking with the funnel.
Test New Data
Internally, you can gather first-person data through your mobile apps, retail websites, consumer shopping profiles, Google Analytics, and myriad other sources. Meanwhile, you can supplement this first-person data with third-party data, adding greater value to your first-person information by placing it within a macro context. Through a combination of data analysis and trial-and-error, you'll be able to identify data types that accurately indicate intent, which your marketing strategies can use to become more proactive.
If, for example, new data reveals that a high percentage of people who visit a given product page multiple times end up making a purchase, you can use a personalized ad strategy to more effectively drive those conversions in less visits. Or if you learn that customers tend to frequent your business after work on their commute home, you can start offering deals during those hours to entice more people in.
Study the Insights
Intent data can help any company better understand consumer behavior. The trick is execution. Last year, eMarketer reported on a Forrester study that found that 67 percent of marketers were confident that intent data could improve strategy and performance, but many marketers struggle to effectively apply that information. Fifty-six percent of respondents said the data was inaccurate, and 48 percent said the attribution models were too complex to implement.
Marketers need better application strategies to get the greatest value from their data. Verifying the data's accuracy is paramount: You should eliminate data channels that have proven unreliable, as these can corrupt your knowledge of the consumer. As a good place to start, consider implemeting campaigns on platforms which offer first-party data insights. While more difficult to integrate into the larger picture of your customer, you will get a more accurate sense of how your campaign messaging is resonating with a particular user base.
Perfect intent-based personalization won't come overnight, but as you get acclimated to new ways of using consumer data, you can begin to build mobile campaigns that are smarter and more productive.
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1. Mobile devices have enabled a range of channels to gather intent data.
2. Marketers should build personalized ad campaigns based on intent data.
3. User-intent models, website content aligned with intent, and intent segmentation can simplify targeting and optimize campaigns.