If you’re a data-driven marketer tasked with efforts like targeting, personalization, campaign strategy, and product development, you’re likely short on time, but abound with data sources. These sources, which we’ll delve into more later, may include:
- Interest data
- Location data
- First-party data
- Transaction data
- Survey data
- And more
Each of these resources can individually help you build a picture of customers in terms of their user experience and purchase journey. They can also complement each other to generate an even stronger picture of customers.
That picture, however, changes frequently these days. If you’re looking to track shifts in interests, preferences, and lifestyle traits, interest data is inherently well-suited for the task as a standalone data source or for data enrichment.
Why Are Consumer Interests Continuously Changing?
To be sure, the way we act and the things we buy have never been static. We’re constantly recalibrated by technology, societal norms, and our obsessions with shiny new things. But today, content that can influence our behaviors and purchases is both accessible and plentiful online.
In addition, our world is constantly being disrupted. We’re still facing the repercussions of the pandemic, for example. McKinsey & Company found more US consumers are switching brands and retailers in 2022 than in 2020 and 2021. Many are looking for value amid rising inflation and are switching to private-label products. McKinsey discovered another interesting shift: A brand’s purpose is now less of a buying consideration for consumers than it was two years ago.
There are many other ways consumer interests are shifting quickly. Among them:
- 52% of respondents reported they were more eco-friendly than they were six months prior, a December 2021 PWC survey found.
- 56% of respondents said healthy eating had become more important to them during the pandemic, according to a February 2022 KPMG survey. Likewise, our own data reveals a growing interest in healthier food and beverage choices.
- Nielsen says the average weekly time people streamed video content in February 2022 jumped 18% from February 2021.
- Cars.com says searches for electric vehicles on its online marketplace jumped 173% from Feb. 24 to March 25 as gas prices rose and the war in Ukraine erupted.
Why Interest Data is Such a Useful Resource
People signal their cross-interests, passions, and changing buyer preferences when they take actions like sharing content, searching information, clicking links and photos, and viewing web pages. Data providers can collect these billions of signals per month across verticals.
Interest data captures real actions that real people take. Plus, it can be collected in real time. Real-time data adds much-needed context to where consumers are in their path to purchase.
You can use real-time interest data for objectives like:
- Creating audience segments that perform well
- Offering personalized customer experiences
- Obtaining new insights about customers at scale
The Power of Adding Real-time Interest Data to Your Mix of Data Sources
Different data sources have different strengths and limitations. Let’s explore how combining interest data with other data sources can help you gauge changing interests.
Location Data
Location data, which is gathered from cell phone signals, can help brands that have physical locations—like retailers and grocery stores—understand their foot traffic. It also does a great job of telling marketers where customers have visited.
However, location data doesn’t reveal what prompted someone to go to a particular place—or to stop going.
Real-time interest data, which captures the research phase of a customer’s journey, can help surface the reasons behind a visit. A homeowner at a big box store who has recently researched and shared content about design trends could very well be renovating their home.
On the flip side, interest data can help brands understand a decline in visits. Someone searching for at-home workout equipment may not intend to renew a gym membership, for example.
First-party Data
First-party data is information that marketers collect directly about their customers through the company’s websites, mobile apps, social media platforms, and other means like loyalty programs and call center conversations. This valuable data includes shopping, spending, and demographic information—and it’s becoming increasingly important as marketers prepare for the deprecation of the third-party cookie.
However, marketers can only access interactions customers have with their company. A hospitality brand with vacation resorts, for instance, only knows which customers have researched its own resorts online or booked stays at its properties. Scale is a chief limitation of first-party data for companies that don’t happen to be walled gardens with massive amounts of closely guarded information about users.
Real-time interest data can help fill the gap. It can provide marketers with a broader understanding of customers’ interests because it’s gathered across thousands of sites on the open web. With access to interest data, the hospitality brand could learn which customers have been researching jungle expeditions or beach adventures. These kinds of insights could inform the brand’s targeted campaigns.
Transaction Data
The information gathered from transactions is a subset of first-party data and is useful for cross-selling, upselling, and other means of engaging with customers. You can gain insights that include:
- How much buyers paid for a product or service
- Which brands they chose
- How many products or services they bought
- Which products they returned or exchanged
Yet, as a historical data point, transaction data only tells marketers about a past purchase and action. It represents the end point of a customer journey, so it isn’t valuable in terms of inserting a brand in the consideration phase that comes earlier. In addition, transaction data doesn’t reveal much about context—marketers don’t know why someone made a purchase or a return.
Real-time interest data can help broaden the picture. It is constantly collected and can signal someone’s current interests and persistent engagement rather than past interests and past engagement. It can also reveal someone’s broader interests beyond a purchase.
A sporting goods store knows a customer has bought a basketball, a basketball hoop, and youth basketball shoes, for instance. Would that buyer be receptive to ads for baseball gear and apparel as well? It’s hard to know based solely on transaction data, but interest data can help answer the question. They likely would be interested in baseball-related products if they’ve also researched baseball equipment on other sites and shared posts about youth baseball leagues.
Survey Data
There are so many ways to use data derived from surveys.
One of the strengths of survey data is that it’s based on information provided by an actual person. One of its downsides is that people may not answer honestly. Results can also be skewed by other factors, like biased survey questions. In addition, survey results can take a long time to gather and analyze, and it’s hard to achieve massive scale with survey data.
Real-time interest data can add context to survey responses and offer quick access to actionable granular insights that can be shared at an event or user level.
For example, while a survey can tell you people are concerned about inflation, ongoing interactions can provide timely insights about consumer trends related to it. Marketers may see that customers have been researching more private-label products over the past month, for instance.
Interest Data Provides Answers About Customers
So as you can see, real-time interest data is not only an effective data source on its own, but it also plays well with other kinds of data.
It offers the context, recency, scale, and accuracy that marketers need to achieve a more holistic view of customers and track their ever-changing interests and preferences. Interest data is ultimately a reliable tool in a time of persistent disruption.
