November 21, 2017
Dan Peacock, Vice President of Product Strategy
If merchants want to remain relevant within their industry, it is essential for them to observe, evaluate and adopt emerging trends for long-term success. As technology becomes more digitally influenced, success will increasingly be dependent on embracing data and analytical tools. The power of using good and relevant data to make informed business decisions is very clear; winners will be the merchants that partner with processors that provide the analytical tools necessary to use their data most effectively.
The data needed to grow a business is certainly out there- the question is how best to gather, analyze and utilize it. Merchants must ensure that they can harness everything from the different channels and devices their customers use: How are customers surfing the web? What are their life-event plans? What is their social media activity? Which YouTube channels do they subscribe to? Some of this data is highly pertinent to buying patterns and represents strong predictors of future purchases, which can be acted upon. The problem is that such data must be presented in a pragmatic and usable format for merchants to truly take advantage.
With the proper analysis of historical information, merchants can clarify which products sell well together and optimize marketing campaigns that reach new customers, deepen relationships with the most profitable customers and increase sales. Merchants who fully understand their customers’ behavior can even extend tactical offers that encourage larger spends at the point of sale from their best customers. Gathering all available data points into a central data warehouse is the first step. The next step is to ensure you possess the latest software to help your team digest the data in a way that drives business decisions and marketing offers. Traditional data sets simply listed the number of returns, declines, and chargebacks – that doesn’t provide a merchant with the intelligence needed for growth. When considering different service providers, retailers must select a partner based on their ability to gather a wide array of pertinent data and present it in a clear and pragmatic way that allows meaningful decisions to be made and acted upon.
Today’s leading analytic software providers offer cloud-based SaaS offerings. The best partners are now able to provide retailers of all sizes with analytic tools that help make sense of the data and guide decision making. Furthermore, with data virtualization, retailers can now access this data in real-time, from any device.
Going forward, merchants that differentiate themselves from their competition with advanced data mining and analytics capabilities will become the market leaders. Applying artificial intelligence and machine learning to data and analytical tools is no longer a futuristic proposition. These types of services use natural-language technology to help businesses identify problems, recognize patterns, and gain meaningful and predictive insights into customer behavior. Ultimately, that translates into increased sales. Which customers are most likely to buy which products and through which channel? Such analytical decisions used to be hard work and labor intensive, but they can now be automated to provide recommendations in real-time.
The equation is simple: The right data filtered through the right tools results in more sales revenue. Advances in technology now mean that SaaS-based cloud services for data warehousing are much more feasible and affordable than ever before. Merchants of all sizes can now harness data from a huge variety of sources to make real-time, knowledge-based business decisions that grow business.
Even better, the cost of data and analytical software is dropping drastically. Five years ago, only the largest retailers could dedicate staff and submit IT budgets to play in this game. Now, software prices have fallen to the point that even small retail operations can afford to build a business based on data and analytical tools for a reasonable amount.
The need for strong partnerships extends into the wider innovation space, and merchants from all sectors are working actively to help drive innovation across their infrastructure and front-end services. With many merchant sectors operating on already tight margins, working with partners who understand their market verticals and have an emphasis on an easy integration process is proving critical.
Only by incorporating big data, adaptive models and AI/machine learning into simple and straightforward tools can merchants build a long-term omnichannel strategy that gives customers a consistent and meaningful experience across all channels. Modern customer-centricity involves a blend of data from an ever-expanding number of devices, channels, and transactions in real time, and results in the delivery of highly-targeted offers to consumers across all channels seamlessly.
However, merchants and their processing partners cannot afford to rest on their laurels. As the cost of technology falls and the amount of data and the number of channels in which it is collected grows, it becomes inevitable that retail will move from omnichannel towards truly anticipatory, customer-centric, highly localized and personalized shopping experiences.
Vice President of Product Strategy
Dan is a member of FIS’s Payments Product Strategy team and focuses on developing the long-term strategy for U.S. retail payment products. His background spans 19 years in financial services leading co-brand credit card programs in the retail, travel and loyalty sectors, as well as issuer-branded consumer and business card programs.
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