On June 8, 2020, The National Bureau of Economic Research officially declared the U.S was in a recession. The pandemic pushed companies to adjust their business models and the way they reached out to and interacted with customers.
The lack of personal interaction presented many challenges. With the shift to digital and online channels, companies needed data to understand customers. Organizations leaned heavily on analytics and machine learning to try and predict customer behavior, buy or churn propensity, and tackle the growing rate of fraud.
Fintech and digital-first companies had a significant opportunity to capture the market share during all this. Data-driven decisions were the key to quickly identifying and processing the needs of customers. But there was a challenge: the data companies had in-house was not very useful.
What Happens When Your Data Is Irrelevant?
Think about it. Data teams had created and trained all their analytics and machine learning models based on specific data sets for certain market conditions. Then the pandemic changed the rule book. The B2B credit models and loan underwriting models weren’t working any more. Businesses were closed for months, and when they opened, foot traffic was scant.
Companies had to scout for alternate data sources and build new models to make smart decisions about lead generation, demand forecasting or credit and fraud mitigation in this new age. Incorporating external, alternative or third-party data became a critical step in making these decisions. For instance, fintech companies processing small and medium business loans started to leverage data signals such as online reviews, web presence, online payment capabilities, web traffic, delivery services to determine the creditworthiness of the businesses.
As we start to see some light at the end of the tunnel, expectations are rising the recession will be V-shaped — meaning a quick recovery following the steep decline. That would be great news for the economy, for employment and for consumers wanting to resume their favorite activities. However, the rebound will present similar challenges to the shutdown, making data teams question whether they have the correct data for accurate predictions. Data scientists may feel a sense of déjà vu: the models and information they have been working with last year will suddenly not be as relevant. They will need different data to improve the performance of their models.
Related Article: Do Data Lakes Live Up to Their Promise?
A Changing Landscape Requires a Fresh Approach to Data
As the economy recovers — whether V, U, or W shaped — businesses will have to respond fast. And they’ll need the current, accurate and relevant data to do so. The consumer goods and food and beverage verticals are in the thick of this very challenge. The small business landscape — restaurants, convenience stores, bars — is unrecognizable. Businesses have closed, changed ownership or are operating at different volumes.
Change is constant. Beyond the pandemic, the loss of third-party cookies and Apple iOS14 changes will force dramatic shifts in marketing data acquisition strategies. Marketers will have to find alternate ways and broader data sources to understand their customers and provide them with the relevant information and personalized service.
In the McKinsey Digital article “Harnessing the power of external data,” the authors wrote: “The COVID-19 crisis provides an example of just how relevant external data can be. In a few short months, consumer purchasing habits, activities, and digital behavior changed dramatically, making preexisting consumer research, forecasts, and predictive models obsolete.”
As CDOs and data teams rethink their data strategy, they must include external data acquisition as an essential component. Seventy-nine percent of data leaders said external data is critical to their business, and 81% mentioned they spend more than $100,000 per month on data acquisition according to a recent survey by my firm. Having an efficient approach to accessing valuable data — and integrating it into your predictive models — will determine how agile an organization will be.
The companies with the right data, a lot of which will come from outside their four walls, will have the first-mover advantage to capture customers (and, ultimately, greater market share). Companies with the right geo-spatial data, foot-traffic data, median income, demographics, business filings and socio-economic data will be able to quickly and accurately find customers, evaluate them for credit or fraud risks and prioritize them in their sales force. They will have a huge leg-up in building new relationships with customers by supporting businesses coming out of the recession. The opportunity is tremendous if you know where to look.
Related Article: The Demise of the Cookie and the Rise of First-Party Data
Ajay Khanna is the CMO at Explorium, the automated external data platform for advanced analytics and machine learning. Previously, he was the Vice President of Marketing at Reltio.
