Data can transform the way businesses make decisions and develop products. According to McKinsey Global Institute, data-driven organizations are 23 times more likely to acquire customers, six times as likely to retain customers and 19 times more likely to be profitable.1 A Salesforce and YouGov backed survey found that in the wake of the COVID-19 pandemic, more data-driven companies (63%) are optimistic about the future health of their business in the next six months than non-data-driven companies (37%).2
Here are 3 ways solutions providers can use data to transform their products and enhance user experience.
According to PwC’s Global Data and Analytics survey, highly data-driven organizations are 3X more likely to report significant improvement in decision-making.3 Tech companies and data providers can help their customers make better decisions and attain their business goals by providing them with data that is comprehensive, accurate, updated frequently and easily integrated into their systems or products.
Use case: A local analytics company delivers enhanced building insights using Data Axle business data
A local analytics company provides its customers with access to a platform that they can use to gain more insight into businesses and/or consumers in their area. Their customers use the platform for a variety of purposes, including market segmentation in a specific geographical area, prospecting to reach new customers, site selection to decide where to put a business, or even indexing for building out a new neighborhood.
Leveraging Data Axle’s data, the local analytics company improved the insights their customers could access by adding comprehensive business and consumer information such as which businesses are inside a specific building, the square footage of each office, how many employees are employed by each business, which buildings have high leasee turnover and which industries cluster in which buildings or locations.
There’s a difference between a fad and a legitimate market trend and data is the only way to truly understand and account for the difference. The onset of the COVID-19 epidemic in March of 2020 has changed the way we do business. Consumers need different services and products and the best way to reach audiences has shifted. To keep up with COVID’s impact, technology providers can ensure their platforms have access to reliable, real-time data on business status including recent disruptions and changes (out of business, suspended operations, open for business) etc.
Use case: Financial services companies predict risk in a changing marketplace
Financial services companies use predictive models that rely on historical data to predict the future, for example assessing credit risk and stock price forecasting. The COVID-19 pandemic has resulted in massive market and economic fluctuations and reduced stability in certain industries. Financial clients need a large quantity of very specific data from their data providers – such as real-time transactional data and movements in current-account balance. Layering this data with firmographics that indicate which types of businesses are opening/closing, how many employees they have and where they are located helps finance companies identify economic trends. This data is especially important when looking at industries affected by this crisis, such as hospitality and travel, as it can help predict which businesses will stay afloat through the crisis and which will need to default.
McKinsey’s sector analysis shows which industries are most likely to default on loans.
Use case: An alternative lender reduces risk by using Data Axle to improve modeling
An alternative lender (meaning, a lender outside of the traditional banking system) turned to Data Axle for additional business data. The lender focuses on small businesses who have been open for at least 48 months. They use Data Axle firmographic attributes as an input into their model that establishes the credit worthiness of businesses seeking credit. The lender uses data points such as business category, employee size, estimated sales volume, year established and the closed business file, to fine tune their model.
In today’s competitive economic landscape, your customers need enough insights to gain a complete understanding of their customer base. Identity resolution helps you combine online and offline datapoints to figure out a consumers’ identity. This process has become increasingly important as people move across devices — mobile phones, desktops, connected TVs — throughout the day. With Identity resolution, businesses can understand that Mobile User A is the same person as Desktop User B.
ID resolution reconciles all available data points, including those collected by first-, second- and/or third-parties. A unified profile gives marketers a clear understanding of the customer’s identity and user journey, providing an insight-informed, data-driven “single-customer view”, also known as people-based or user-level marketing.
Tech companies and data providers can leverage Data Axle’s data to unify and enhance the multiple sources of data they are using to provide new insights, create better performing models, and drive greater outcomes for their clients.
Use case: Identity resolution and Data Axle’s data
A B2B technology company provides an identity graph leveraged by marketers and advertisers to better target prospects and customers. The company relies on Data Axle’s business and consumer data to overlay information on their current identity graph solution. This helps them link disparate data together to create a 360 degree view of an individual. In turn, this helps their customers overcome ID resolution gaps.
Ultimately, better data means offering a better product and a better customer experience. If you want consumers to trust your platform, you need to fuel it with the best data out there.
Want to know more about licensing data to provide intelligence for your solutions? Download our whitepaper, “5 key elements for building a successful data-driven product.”
Bob Toth is responsible for leading the Data Axle Data Licensing team. He manages the development of new partnerships and business growth within existing partner relationships, including data licensing, joint product development, and reseller channel optimization. Bob brings over 20 years of data related sales experience working directly with a broad spectrum of information businesses, applying data to direct marketing, digital and mobile marketing, commercial credit, commercial risk, insurance, government services, public records, search, navigation, mobile apps and commercial real estate products and services.