Many agencies and brands focus solely on behavioral data and stats from analytics platforms to form a deep understanding of their consumers.
This is a mistake that’s leading to endless missed opportunities.
Coupling this information with rich data that investigates the motivations, attitudes and interests behind their actions removes the risks and means better marketing decisions are made.
Here’s how to do it and why.
Mapping the fragmented consumer journey.
Behavior analytics has changed in many ways, but a big part of the change is that the traditional consumer journey from entry to checkout no longer exists.
It’s now splintered and fragmented across location, channels, devices and more. And despite rising pressure on brands to be present in the right place at the right time, consumers are harder to track accurately.
But not only that, consumers are now demanding a more personalized approach from brands, and are increasingly using ad-blocking software to control their online experience.
This is just one of the many reasons why a one-size-fits-all solution for behavioral analysis isn’t enough for brands to resonate and engage efficiently.
With deep insight, you can track the right footprints and be confident that you know exactly where to meet your consumers, and when.
But you can’t just be in the right place at the right time – you have to provide the content and experience your target consumers expect.
Why? People have different reasons for doing different things. Our data proves it.
Identifying the what vs the why.
What is behavioral analytics? Traditional audience research focused primarily on demographic data that revealed key aspects of the people you’re targeting. This has evolved over time to meet increasing demand for answers that enable more accurate targeting.
Behavioral analytics tools then came on the scene to give marketers the answers they needed, when they were needed.
Despite the importance of knowing what they’re doing, the most revealing insights are born out of knowing why.
Picture this: A UK coffee brand is looking to reach fitness fanatics aged 16-24 promoting their new antioxidant blend.
To get started, they begin analyzing this group with user behavior analytics software to find out where they are, and what they do online. Here’s what they find out about them.
- Use Facebook more than any other social network
- Use ad-blockers a lot
- Follow their favorite brands on social media
- Regularly buy products online
- Follow influencer blogs
These behavior analytics software insights give them a good starting point, telling them which platforms to invest in and sparking ideas on what approaches to take.
But before the campaign can really take off, there’s a lot more to uncover, which means digging into the user data and various data points for their motivations and attitudes.
- Like to use Facebook to research products they want to buy
- Use ad-blockers to avoid annoying and irrelevant ads
- Prefer to discover new brands through influencers than online ads
- Follow brands that share interesting video content
- Are motivated to make a purchase by free delivery and rewards
- Like to follow fitness vloggers
Behavior analysis can provide a wide range of user activity insight. Knowing its target consumers are more likely to discover brands through influencers and share a strong interest in vloggers, the team can be sure of the value in onboarding the right celebrities or micro-influencers.
It also indicates they would benefit from investing in Facebook more than other social platforms, but it would be much more beneficial to do so with entertaining video content, rather than promotional ads – the kind this audience actively blocks.
End result: a sturdy, promising campaign, launched via the right channels, that’s based on fact, not assumption.
Here’s a real-life example.
Insight in Practice: Blis
As a leading provider of location data, Blis is a brand that continues to grow.
Setting its sights on new markets further afield, the team needed access to reliable insights to help them understand the opportunities within.
“Understanding new markets was our biggest challenge”, says Alex Wright, Head of Insights at Blis. “Almost every European market will have their own independent data sources. And when you go further than this, a lot of the sources and data are inconsistent and you don’t know the origins.”
This lack of knowledge put barriers in place for the teams when it came to speaking to these prospective clients and solidifying their pitch.
In an effort to prove to existing and prospective clients they were willing to go above and beyond for them, they invested in GlobalWebIndex. This gave Blis ready access to deep consumer insight they simply couldn’t find elsewhere.
“Before GlobalWebIndex, we could infer why people were doing certain things from their actions, but this meant we relied on people buying into the common sense nature of human behavior. For example, that if you go to a five-a-side match, you must have an interest in football.
“We lacked the active, declarative data we needed to understand consumers’ motivations for doing these things.”
By being proactive and introducing an external data to complement their own, Blis has positioned itself as a business that offers a comprehensive solution, and far more than just location data.
Using insights it uncovered via GlobalWebIndex, the brand:
“This data has strengthened our relationships with our clients by showing them we’re willing to invest in additional sources to help us make more intelligent decisions on their behalf.”
Download the full case study here.
Understanding the why.
Reliable consumer data is no longer a nice-to-have. It’s a crucial part of the puzzle for any marketer looking to compete and can often be very sensitive data.
And as consumer journeys become increasingly fragmented, the pressure is on brands to prove they not only know what their consumers are doing, but why.
This begins with one thing; robust, granular consumer data.
Because when you have access to the kind of data that effectively represents your target audience and presents their motivations alongside their user behaviors, you know the why is within reach.
- Identify the answers you’re missing
- Analyze behaviors
- Explore motivations behind them
- Look into interests and attitudes
- Combine the two for richer insight
- Pull out the big truths