From Latana’s inception, we set out to create a way for small and medium-sized enterprises (SMEs) to track the performance of their brand and gauge how consumers perceived it. That journey has taken us from our original BrandTracker tool to the brand tracking software that, today, helps our clients build their marketing strategies and grow.
In this article, we’ll take a closer look at why we launched Latana, how we built our brand tracking software, and exactly what it allows companies to achieve.
Building On BrandTracker
Let’s start at the beginning and talk about BrandTracker. We launched the product in 2017 and offered brand tracking to SMEs across Europe. This was in contrast to other brand trackers, many of which have been around for decades — but are still mostly used by larger firms due to the prohibitively high cost.
With BrandTracker, we offered a leaner, lower-cost version that focused on a set of standardized KPIs (around 5-10) and smaller sample sizes (usually 500). We delivered insights to our clients on a regular basis, usually monthly or quarterly, through an easy-to-use dashboard.
Some aspects of BrandTracker were received really well by our clients. The dashboard was intuitive and a big improvement over the industry-typical PowerPoint presentations or PDF documents.
Also, the speed of BrandTracker was a big plus. We were able to deliver results within 1-2 weeks, in an industry where clients often wait months to get the first insights. Lastly, our low-touch approach allowed us to keep the prices low. Our clients were surprised how much value they could get for their money — especially those that had previous experience with brand tracking.
But why did we move away from a proven business with existing clients and steady revenue streams?
The answer is that we realized that BrandTracker was not providing as much value to our clients as we wanted and that there was an opportunity to create a tool that could be used to give marketers powerful insights to grow their brand. By harnessing innovative new methodology, we could do brand tracking in a completely new way.
We knew what worked well with BrandTracker, but in order to build a product that truly solved our clients’ problems, we took a closer look at the ways in which it underperformed.
One key learning. Despite giving our clients a high-level overview of how their brand was performing, our user tests showed that most of them did not act on the insights provided. And, to our surprise, we found out that this is the norm, rather than the exception, for most brand trackers.
This is because brand tracking is typically done through quota sampling and, in most cases, the methodology struggles to pick up real-world changes.
Another drawback was that entry-level services that run with a sample size of 500 have a margin of error above 4%, in the best case. Decisions based on these insights should exceed this margin of error, however, this is unrealistic for most brands — as it requires reaching millions of additional consumers in a short period of time.
Then, as now, most brands we worked with did not actively market to everyone. Instead, they have smaller target groups that they focus on — be it in terms of age, gender, location, interest, or other demographic or psychographic criteria. For those that want to zoom in on one of these target groups, the sample sizes become even smaller, the margin of error skyrockets out of control, and the insights become entirely in-actionable.
Ultimately, we knew that we had to find a way to provide our clients with actionable insights to build a sustainable company. So, it was time to move forward.
Moving to a New Way of Brand Tracking: Why and How
With an understanding of what did and didn’t work with BrandTracker, we set out to design a solution that would give our clients reliable insights that help them build a thriving brand.
In order to do this, we knew our tool had to give a detailed picture of how a brand is performing in the real world for various target audiences and how that is changing over time.
After months of conceptualizing and prototyping, we concluded that by applying a recent innovation in data science, Multilevel Regression and Poststratification (MRP), we could develop a tool to solves this problem.
MRP had recently gained popularity within election predictions, after those modelers that used it successfully predicted the results of the 2012 Elections election for all 50 US States without actually having representative samples from each state. We decided to adapt it and further develop it as a means of tracking brand performance for the benefit of consumer brands.
How MRP Revolutionizes Brand Tracking
MRP is a model-based method. It uses information from the entire sample size, which allows Latana to predict brand awareness based on a respondent’s characteristics. In other words, we use it to estimate the brand awareness of someone in any given target audience.
To demonstrate, let’s use vegetarian Generation Z-ers who are active on social media as an example. MRP looks at all respondents who report being active on social media, all vegetarian respondents, and all Generation Z-ers in the sample.
Because the amount of respondents that fit all three characteristics is likely to be very small, it combines the effects of these characteristics to produce an estimate for respondents who have all three characteristics — our target audience.
By using the entire sample to build the model, the estimate for the target audience is actually very precise, even though there are only technically 20 respondents of the target audience in the sample.
MRP’s key benefits, compared to traditional brand tracking, are the following:
We can retain high precision even across niche audiences, where traditional, entry-level brand trackers would fail
It is optimized for tracking, which means we are much more likely to pick up real-world changes, instead of being distracted by any noise in the sample size
Running MRP is a very complex exercise and only a few firms in the world have the ability to do it. Since the model gets more accurate with more data, to make it work, large sample sizes are required.
Here it helps that we can access millions of respondents at the tap of a button. But data collection is only the first part and is followed by a computation-intense algorithm. When we started using MRP for Latana, some of the initial projects took us 3-4 days to compute, which is why we used to run them over weekends.
While we have solved these initial issues around scalability, the resources required to model the insights are still immense and far from trivial to execute.
Designing a Brand Tracking Platform That Empowers Our Clients
Now that we could provide our clients with powerful insights drawn from MRP, we needed a means of allowing marketers to explore this wealth of data. But marketers are not data scientists, so our dashboard needed to be intuitive and easy to use.
We built our brand tracking platform from the ground up with these goals in mind. With it, users can build dozens of audiences to replicate their target groups and personas and track the performance of their brand over time — looking at brand awareness, consideration, and preference.
This is an absolute novelty in the space of survey-based brand insights, as users typically receive a static presentation and cannot explore the data themselves, let alone have the possibility to analyze dozens of audiences. With brand monitoring, marketers can keep their ear to the ground to chart how their brand is performing, detect changes, and tailor their messaging and advertising towards each of their audiences, maximizing impact and brand growth.
We’ve put in a lot of effort to ensure that the dashboard is accessible and easy to use, so you can track your brand’s performance with different target audiences with just the click of a button.
We’re always seeking to improve our brand tracking platform, but already it provides our clients with in-depth insights across audiences, helps them understand how their brand is performing, and precisely measures the impact of marketing activities.
While it tackles a similar problem, our dashboard is a quantum leap ahead of traditional brand tracking and the benefits for marketers are plentiful:
Measure the real-world impact of marketing campaigns on your brand
Understand how your target audience perceives your brand and how that compares to other audiences, all of which you can do with high precision
Detect entirely new audiences that respond well to your brand, which you were not aware of yet
Target your marketing to various audiences and measure the impact, instead of treating everyone the same
Understand how you fare against the competition, on a granular level, learn from them and avoid their mistakes
Final Thoughts
Moving away from quota sampling toward MRP has opened up seemingly infinite possibilities and we have a lot of exciting features in the pipeline. Expect more cutting-edge innovation in a space that has been largely free from it for a long time.
Updated by: Ashley Lightfoot on 11.03.22
