For Retailers, 'Small' Data is the Key to Impactful Personalized and Localized Campaigns
Personalization might be the word of the year for retail marketing. As technology has evolved, retailers are now able to scale local promotions to maintain the reach that only national promotions in a bygone era of big TV commercial budgets and Times Square takeovers would have delivered.
It’s widely known that consumer preferences have shifted to favor instantaneous, relevant interactions with brands and retailers. In fact, when done right, McKinsey reports that personalized promotions can provide a substantial benefit of 4 percent to 8 percent sales increase and 2 percent to 3 percent net income, and earnings before interest, taxes, depreciation, and amortization (EBITA) uplift. The pandemic, new generational preferences, and the expanded role of digital technology in our everyday lives has amplified this. Layer inflation concerns on top, and retailers have quite the puzzle to piece together on how to connect with and effectively provide value to their customers.
That’s where good, granular data comes in, also known in some circles as “small” data. Planning an effective retail promotional campaign for today’s changing consumer is about far more than just grabbing all the data available and rolling out the same message to a broad nationwide audience. Instead, the most impactful and effective product success at the local and regional levels benefits from taking insights down to more microscopic views to inform specific and tailored campaigns. Let’s take a look at how.
Dissecting Loads of Data to Get the 'Right' Data
Global data creation is projected to grow from 64.2 zettabytes in 2020 to more than 180 zettabytes by 2025. With the reality of multicloud, this enormous data load can be manageable, and it may be just a change of mindset (and data management tools, of course). Instead of analyzing one big data source, retailers should focus on pulling the “right” data from individual clouds and systems to blend and understand local and regional campaign needs.
For many retailers that have shifted from product-centric to customer-centric strategies, this requires the business to prioritize customer insights and re-evaluate the customer journey from top to bottom. Identifying what motivates your customers, what their pain points are, and how they shop (multichannel, of course, but is it phone, computer, store, or a different combination of channels) should give a clear indication to what you should be looking for. And paired with all the systems retailers require — TPS, POS, CRM — the right data will be there.
Optimizing for a Customer-Centric Approach
As a customer-centric retailer, one of the best ways to optimize your marketing efforts is to ensure that you aren’t applying mass market data marketing management and analytics to your customer-centric model. Using a small data approach, with the right data, is how you can craft promotional plans that are as relevant as they are timely. In my client SodaStream’s case, when armed with the right consumer data, it was able to dynamically create audiences that feed further intelligence into its marketing automation platform.
In one example, SodaStream could have millions of contacts, but really only want to look at those who have purchased flavored products in the past two weeks across the Northeast region — somewhere they might have a retailer partnership or an abundance of supply and want to move product by sharing a promotional offer with the most engaged shoppers. To do so, it would use its customer data to dynamically create audiences to feed further intelligence into its marketing automation platform, which would then target the right shoppers in the right city at the right time.
From a marketing perspective, when all the ideal tools are in order and business goals are clear, the process can be as streamlined as ensuring the right data is coming in and that the architecture is in place to use it most effectively.
Gain More by Getting Granular
The one thing we know for sure is that change is constant. This definitely applies to today’s consumer as the way we live, shop and work has changed so drastically over the last couple of years. Retailers embracing the new digital economy will take strategic advantage of what the data is giving them — an opportunity to really understand and build customer relationships on a very localized level. It’s time to get granular.
Poornima Ramaswamy is executive vice president, global solutions and partners at Qlik, a data analytics and data integration solutions provider.
As the Executive Vice President of Global Solutions and Partners at Qlik, Poornima leads a multi-disciplinary team that blends alliances/channel strategy, consulting and education services, as well as value engineering. Her team designs and executes transformational strategies for large enterprise customers to maximize the value of their overall investments in Qlik’s data integration and analytics platforms. In her position, Poornima also holds a leadership role within the Customer Exchange Network.
Poornima joined Qlik from Cognizant, where she was the business leader for their AI & Analytics practice in North America. During her tenure, Poornima also led the Cognizant Chief Data & AI Officer Advisory Council, a community of analytics executives focused on AI & Analytics as a strategic imperative for organizations. Poornima has more than 20 years of experience across a variety of industries and started her career at Tata Infotech.
Poornima holds an MBA from ICFAI Business School, India and a BS in Mathematics from University of Madras, India.