When analog T.V. reigned supreme, cable companies promoted their new lineup of shows with simple ad strategies: pick a time and date that the designated audience—defined by age, gender, and region—would be watching T.V., and run the promo then.
When marketing went digital, many of these same tactics transferred over. Just like the cable companies, marketers ran campaigns based on broad demographics like age and region, or surface-level information like page visits and ad clicks.
This type of marketing has been the norm for decades. But what digital disruptors like Netflix realized is that there’s a much more effective way to construct audience campaigns: with first-party behavioral data.
Behavioral data is data about customer behaviors—where a customer found value in the digital product, what their holistic customer journey looks like, and what activity motivates them to return to the product over time. First-party behavioral data comes directly from the company’s app or website and is sent to a product analytics solution, where digital teams can explore the data to find these key customer insights. In other words, there’s no reliance on a third-party service to get information about what customers value.
By constructing campaigns around customer insights—rather than demographic data—companies like Netflix have disrupted entire industries. Instead of targeting a broad demographic group, Netflix makes recommendations based on demonstrated behavior, like previous shows watched. Personalizing the customer experience by determining, “Since you finished these three shows, you’ll probably enjoy this one too” is much more effective than watered-down personalization attempts that assume, “Since you’re in this age group, you might like this show.”
This level of personalization that Netflix achieves—similar to ad strategies and content recommendations employed by Amazon and Spotify too—might seem out of reach for most marketers. But in fact, it’s actually quite possible. The key is to move away from a reliance on third-party data and demographic information. Instead, marketers need to embrace product analytics as a means to access first-party behavioral data, and truly understand which offers motivate customers.
Access to Third-Party Data Is Changing
Apart from the more comprehensive insights marketers can get from first-party behavioral data, there’s another reason they need to move away from third-party data: Google and Apple have recently implemented privacy protections for customers, which inhibits third-party tracking about website visits, app downloads, and ad clicks. Google has announced that it will end the sale of ads based on tracking user data across websites. Similarly, Apple’s latest iOS will require implementing “opt-in” consent before tracking users.
In other words, when it comes to running ads or retargeting campaigns, marketers should leverage the data they have—first-party data about which messages or features different audiences respond to—rather than relying on a third-party tracking service.
And while third-party tracking may have helped marketers understand which sources their customers are coming in from, this is another gap that product analytics can fill. Product analytics solutions like Amplitude use Identity Resolution to create a full picture of the customer journey. This means that if a customer visits the website, but later saw an ad and then visited the company Instagram page, and then later on converted and signed up for an account, Amplitude can merge these anonymized user journeys into one, showing how how one customer engaged with the brand from three different streams, all of which contributed to the final conversion. In other analytics platforms, this single customer would appear to be three different customers, and it would not be clear how each channel and interaction contributed to the conversion.
Considering data-sharing updates and gaps in the information provided, third parties can’t be your sole sources of customer insight. Leveraging first-party data with product analytics is the best way to get a complete view of the customer journey and use those insights to produce outcomes.
How the Marketing Team at Current Uses Product Analytics to Understand Customers and Inform Campaigns
Take Current, a banking company that’s disrupting its field by putting the customer experience first. As a digitally native challenger bank, Current keeps its teams focused on understanding customer behavior and driving customer-centric outcomes.
“It’s all about understanding our audience,” Adam Hadi, Current’s VP of Marketing said. “We need to understand why a customer needs the services that we’re providing and how we’re fulfilling that. Qualitative research is extremely important, but data is the backbone.”
To this end, the marketing team at Current leverages behavioral data about product engagement to plan their campaigns.
They use Amplitude to investigate which features and messages drive the most engagement within the app, and then they use that behavioral data to inform exactly which ads they run, which audiences they target, and which messages they write. They can target an audience segment that has demonstrated high engagement with a particular app feature and ultimately ensure that their ad budget is spent efficiently by sending the right message to the right person at the right time. They can also plan marketing campaigns around the features that have demonstrated the most success with driving customer loyalty.
Marketers at companies like Current have embraced the digital-first mindset. They recognize that the key to driving business outcomes lies in understanding customer behavior. Product analytics—with its depth of insight into digital activity—reveals far more about customer motivations than simple web metrics or customer surveys ever could.
Behavioral Insights Fuel Marketing Personalization
Product analytics helps you understand what users’ behaviors say about their intent. Once you know why someone is taking an action, you can set up your marketing to be relevant to their unique product needs.
At Amplitude, we have seen customers bring their product analytics to the forefront of marketing efforts.
- Retargeting: Marketers can encourage users to return to the product or company site based on their unique actions. For example, you can use Amplitude Recommend to automatically send behavioral segments in Amplitude to ad networks, marketing automation tools, and personalization engines for retargeting. You can define behavioral cohorts based on the actions that they have taken, or not yet completed. By creating cohorts, such as customers that are not yet paying, you can target a more specific audience with your ads.
- Aha moments: When customers reach their aha moment within your product, send an email or use in-app messaging to encourage further usage. In products like fitness or meditation apps, that aha moment may occur when customers complete their first full exercise routine on a free trial. That is the moment to reach out to the customer with a subscription or special offer.
- Personalize the Customer Experience: Customer expectations have never been higher, yet for many companies personalization can be hard to wrangle. Complex data collection and meaningful personalization seem like overwhelming tasks for technical teams and marketers. Amplitude Recommend provides self-serve insights that allow teams to find the right message to deliver the right users at the right time.
Then, by using product analytics like Amplitude, you can measure how customers are responding to your targeted marketing efforts. You can segment customers by campaign, channel, or behavior and see which methods produce the most engagement over time. The marketing campaigns that result in higher lifetime customer value can be prioritized for future campaigns.
Product Analytics: The Foundation for Personalized Recommendations
Marketing based on broad assumptions about customers may seem like the easy route, but it only creates more difficulties down the road.
Without a clear target audience, you will probably spend more money than needed to reach potential customers who match your ideal customer profile. Not to mention, you’ll also risk losing out on customer loyalty by casting a wide net when you could create a more personalized experience.
While product analytics builds the foundation that you need for understanding your customers’ behavior, leveraging that data for a personalized customer experience will take those insights to the next level. With Recommend — a new product from Amplitude —you can customize the product experience to drive your marketing efforts forward.
You can create cohorts based on any events that your customers have performed in the past, such as adding to cart or starting a subscription, to trigger engagement-based marketing conditions. From there, powered by Amplitude’s AutoML system, you can create the right assortment of recommendations, from content to products to messaging.
Request a demo of Recommend to learn more today.
