Pinpointing your high-value, high-intent users with behavioral marketing analytics is the equivalent of using a laser pointer instead of a floodlight: instead of offering more content to everyone all at once, you can provide the right content to the right audience at the right time.
In this highly personalized digital economy, marketers need to compete by selling directly to individuals, not to nameless brand personas generated from demographic data. Once reliant on unreliable web analytics, marketing teams no longer need to base campaign strategy on blind hope after launching a massive campaign. By using digital optimization tools like Amplitude to analyze user actions, preferences, and tendencies, you’ll have a greater chance of personalizing experiences and communicating value to users who actually care.
What is Behavioral Marketing?
Behavioral marketing is a strategy that digital-savvy teams employ to find out exactly what users value and desire. By focusing on a user’s behavior, you can develop a deeper understanding of how to communicate your product’s value. Behavioral marketing relies on data that’s created when users take certain actions; for example, filling out a form, requesting a demo, or clicking a button are behaviors that reveal intent and motivation.
Paying attention to these movements gives you rich insight into how to improve every stage of the customer lifecycle. The ability to edit your funnel’s content and messaging in real time enables accurate personalization and a more natural user journey. Instead of batch-and-blast tactics like mass email storms, you can take a targeted, strategic approach by focusing on the “digital body language” of users.
Behavioral marketing can help you come up with and answer questions like:
- Pathfinder: What do your users do from the moment they land on your webpage until they decide to make a purchase? If there’s a pattern of behavior before a purchase, key in on that to see what customers value.
- Time to Convert: How long do they stay on a certain section of the webpage? Using heat maps, you can determine the most engaging areas of your webpage and find out why they’re working.
- Engagement Matrix: Which banner images garner more CTA clicks? Sometimes small modifications like changing an image can garner more engagement.
- Conversion Drivers: Does multi-device activation create a conversion drop-off? By targeting user behaviors, you can find the friction points that prevent users from moving further into the funnel.
Yes, behavioral marketing can help you achieve and exceed your business KPIs, but the primary focus is on optimizing the user experience by delivering what’s valued. If you can provide a highly personalized user journey, other goals like conversion and retention will soon follow.
3 Tactics for Your Behavioral Marketing Toolkit
Target the Right Audience with Behavioral User Segmentation
Hypothetically, if you ask a room of people if they like fruit, a lot of them will probably say yes. If you ask those same people if they like watermelon, you’ll likely get a different number. Here’s the takeaway: not all people who like fruit like watermelon. The same logic here applies with targeting the right users: by segmenting the room based on this difference, selling watermelon just became a bit easier.
You can use behavioral segmentation to separate users and customers into specific groups based on how they interact with your landing pages, ads, emails, or digital products.
Event segmentation is important because it helps you navigate the key differences in motivation among your users. Superficial data points like age and location only tell you who your users are, not what they want from interacting with your product. Once you find differences in what certain user segments value, you can then design user journeys and experiences that align with their specific behaviors and preferences.
For example, perhaps you’re trying to get users to download a whitepaper. After segmenting your users based on levels of engagement, you realize that one segment downloads more whitepapers than other segments. You notice that the heavy downloaders are interacting with a brand-new landing page. In this instance, you may assume that the fresh homepage banner and minimal copy are increasing downloads. You can then validate that theory by presenting the fresh layout to other segments of users. Once you find a winning formula, you can then increase overall downloads by exposing this whitepaper to all user segments.
Stay Nimble with Real-Time Analytics
As consumer economics and trends shift, so should your marketing strategies. Staying ahead of the competition in the digital world requires speed. Real-time analytics can bridge the gap between receiving information and making decisions. When users interact with your landing page, mobile app, or email, data is recorded and displayed within a virtual dashboard, giving you the opportunity to make changes within seconds. A quick response time gives you more chances of sticking to what works and removing what doesn’t.
For example, perhaps you decide to use Amplityude’s real-time analytics on a new marketing campaign. You utilize Microscope and notice that out of several styles of CTA buttons, one version is performing exceptionally well. Instead of waiting for the end of the campaign to collect data, you can now double-down on a winning feature by changing the low-performing CTA buttons immediately.
When it comes to paid advertising, every dollar spent counts. Another way to use real-time analytics is by using Amplitude’s Revenue LTV chart. There, you can begging measuring your own spend on ads compared to the performance of said ads. For instance, if a Facebook post starts to gain traction based on the Revenue LTV results, one could easily make the case for more budget and extending the life of the ad.
Confidently Place Digital Bets using Predictive Analytics
As you might imagine, knowing what a user will do before they do it is valuable knowledge to marketers. Thanks to advances in Amplitude’s predictive intelligence, you can now tailor your user journey and messaging based on probability.
Over time, every user and customer action can be ingested, measured, stored, and queried. User actions such as clicks, page views, downloads, abandoned carts, song plays, search results, external shares and more are all examples of valuable behaviors to measure and analyze. This means that predictive analytics will grow with your business over time, and around the 10 to 12-month mark, you should be able to confidently make well-informed predictions about how your users will react to a new feature, CTA, feature, or email.
Put another way: Amazon is notorious for presenting accurate recommendations using predictive analytics. Amazon users’ purchase history, preferences, time spent, and recent web actions all feed their predictive formula with valuable metadata. The result? Their users buy something they didn’t even know they wanted while also providing the algorithm with more information to further influence buying habits. Using Amplitude’s Recommendation engine, you can drive conversions with true, one-to-one personalization based on existing user actions.
Predictive analytics can also be used within email campaigns to send individualized marketing content. For instance, if a user abandons a certain kind of item in a cart, Amplitude’s predictive intelligence might suggest a similar item that could be closer to what the user needs. According to Salesforce, chances are high that the user will turn into a customer once they receive a reminder email featuring their abandoned items.
Democratize Access to Behavioral Data
Let’s assume your marketing team just used behavioral data to inform their strategy on a new campaign, and it was a huge success. Based on their results, it would only be natural to infer that other teams can experience similar successes with behavioral analytics. To get the most out of this investment, share access to your user behavioral data with other teams throughout your company, and watch the ROI blossom. User behaviors create patterns of authentic intent that tell a story: what a user values and how they behave when they want something.
Product, Sales, Design, and Customer Success teams can use that same (now democratized) user data to become more familiar with the wants and needs of those newly acquired customers. In the best case scenario, said teams can work together in a shared Team Space, or individually in their own team-specific workspace. In the end, this cross-pollination of data helps the business offer a superior product.
Continue your learning about behavioral marketing and behavioral analytics. Read the Retention Playbook today.