There’s so much you can learn from your customers’ digital footprints – including how much to spend and where, to maximise business returns.
Imagine you are the Brand Manager of a Fortune 500 automotive brand planning to penetrate a new market in Southeast Asia and to set up showrooms.
Anyone with a rudimentary knowledge of the local market can tell you which areas all the luxury or affordable automobile showrooms are clustered. So, your first instinct might be to set up shop there, since that particular area is known for having a concentration of car dealerships.
While this isn’t a bad strategy, per se, but maybe we can do better. What if you had data on which income group your buyers belong to? That is certainly a useful piece of information. You could leverage that information to place your outdoor ads like billboards and roadshows, in affluent parts of town – to promote luxury automobiles from Germany, the UK, or the US.
And if you are selling competitively priced cars from Japan, you would probably want to place your showrooms, outdoor advertising, and promotional activities in the middle-income parts of town. Another consideration:
Data-driven insights are not always intuitive, sometimes the truth can catch most battle-hardened marketers off-guard. For example, we recently found out through data analysis that a reasonably priced Japanese brand has more market share from the affluent parts of society, as opposed to the average Joe with a median salary. Seems counter-intuitive, but true, nonetheless.
When compared to this reasonably priced brand, higher-priced Japanese manufacturers have lower affluent market share and higher middle-income market share. In other words, middle- and lower-income groups prefer pricier cars when it comes to Japanese brands, and affluent groups prefer cars that are more reasonably priced!
Now let’s say the marketer has already established a presence in the region and has strategically placed showrooms at seemingly sensible locations. What can data do for them now? Or to be precise, how can data help them predict and plan for foot traffic?
With ADA’s proprietary telco-powered Data Management Platform (DMP), XACT, we are able to access footfall data from customers of all ages, demographics, interest groups, and beyond. It is a fairly large sample size with high variability and rich history, which we can leverage in the form of insights and predictions.
So, if you are trying to anticipate the volume of foot traffic on certain days and hours, certain locations, or even under specific weather conditions, we can create highly accurate simulations from machine learning and data-driven predictions.
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Let’s say you want to market luxury hand-crafted Oxford shoes that are only affordable to the affluent segment. When you create a campaign strategy to increase footfall, it would come in handy to know which malls they typically flock to when they plan to shop for shoes.
Combine consumer’s search history data (example: “Oxford shoes”), with their physical location data, and you can zero-in on the areas where your most imminent customers are likely to be found.
For example, say you plan to increase foot traffic on October 10, 2019 – during the launch of your new line of formal shoes – where you can plan if you know the time window between purchase intent and actual purchase, which could be several hours to several days, even several months in some cases.
Let’s say the window turns out to be three days before, i.e. we find out that people are most likely to search for shoes three days before they make the actual purchase.
These powerful insights will help you to plan and advertise online and launch promotional activities – in areas where your consumers are hanging out, both virtually and physically – three days ahead of October 10!
Are these type of insights you’d be looking for your business?
For a short period, it’ll be our pleasure to show you a demo of this brilliant tool!
With more than 25 years of experience in Consumer Insights, Data Analytics, and Marketing across South Asia and Southeast Asia, Rozy serves as the Regional Practice Head of Business Insights & Analytics. She leads a team of passionate insight experts to provide data-driven solutions and harness positive business outcomes. Her team of data analysts, data scientists, business consultants, and industry experts work closely to collect invaluable data points, build relevant models, and extract the right consumer insights with the aim of driving better decisions in the corporate world.
Deep-diving into customer behaviour, analytics, and consumer insights has resulted in the strengthening of clients’ database via Data Enrichment, streamlining Customer Lifecycle Management (CLM) processes, and delivering Consumer Personas and Next Best Offer Models to trigger usage upliftment.
Previously as the Managing Director of Sri Lanka, she set up the local market operations and led the team of digital experts to deliver comprehensive data-led digital solutions. She has a track record of driving business results and maximizing profitability for over 1000 clients through exceptional digital marketing strategies on multiple platforms.
On a personal note, Rozy is exceptionally passionate about coaching and mentoring, and she looks forward to building the next generation of leaders.
To know about what she does and her plans for Business Insights & Analytics, contact her at email@example.com.