Consumers: we all know they’re demanding when it comes to what they want, where they want it, and when. But what if retail companies could actually use global consumer data – encompassing varying tastes and behaviors down to the local level – and combine it with their own sales data to make accurate predictions and improve decisions? To date, the ability to act on insights remains a sought-after challenge in retail. In fact, a common theme at NRF’s Big Show this past January was that the retail world, as engaged in consumer data as ever, has yet to crack this code. But that’s beginning to change.
Historically, retailers have had a love-hate relationship with data. The opportunities to better serve consumers based on accurate and complete insights come with increasingly complex challenges in gathering, cleaning and analyzing data. As a result, the key to finding actionable insights from data often lies in partnerships where retailers can better access global consumer data and utilize analytics technologies.
“The proliferation of data, accelerated pace of business and rapid advancement of digital technologies has created a global environment where success is dependent on connections,” said Morley. “As retailers navigate this new retail world, we believe that collaboration is a crucial component to omnichannel success. “Our connected partner approach enables a higher level of teamwork and collaboration. We are encouraging connections — not just connecting data, but connecting teams, vendors and media agencies to bring true open source to the retail industry.”
With more access to better consumer data, companies can now approach analysis and interpretation more intelligently, considering both long-term strategies and everyday decision-making to finally put data to use.
Data Consumption Trends
Technology’s impact on the way global consumers engage provides retailers a wide range of views of the consumer. Considering e-Commerce in particular, technology serves as an equalizer for gaining the same kinds of consumer insights for both developed markets and developing markets – the latter being traditionally more difficult for information gathering.
“Consumer behavior and preferences certainly vary per global market and despite the influence of technology, it is important for marketers to continue to learn and leverage those local insights, said Morley. “Nielsen has a global view of the consumer; we study consumers in more than 100 countries to give the most complete view of trends and habits worldwide. And we're constantly evolving, not only in terms of where we measure, or who we measure, but in how our insights can help you drive profitable growth.”
In harnessing data that is most useful, retailers must remember to focus on their core markets and regions at a high-level and identify more granular trends from there.
Prior to the surge in e-Commerce, consumers in developing markets had been far more difficult to understand due to a lack of information — and data sources — available compared to those in more developed regions. Today’s consumer, no matter where they are located, represents an ever-moving target with scaling expectations. Both global retailers and smaller local retailers serving emerging markets now have the opportunity to understand emerging-market consumers in the same way that consumer behaviors in developed markets have been long been analyzed.
To stay ahead of changing preferences, smart retailers and retail marketers are tapping into more personal level data for a complete view of consumers. However, purchase data only tells one part of the story. In order to better understand and predict exactly when, where and how to reach shoppers, it is important to include offline behaviors, media consumption and economic factors that directly impacting shopping behaviors in consumer data analysis.
For example, a view of customer #1’s shopping history may illustrate product, channel and payment preferences. However, if the small Midwestern town where customer #1 resides recently faced damaging weather that shut down local businesses, and customer #1 is now unemployed and facing financial insecurities like other residents in the area, customer #1’s shopping behaviors will likely also be impacted. Without the external factors considered, retailers have no way of knowing the complete story. Considering larger unplanned economic events like BREXIT, this is where the whole new world of measuring behaviors at both small groups and individual levels will offer significant value.
Actionable Insight Challenges
According to Morley, “in today’s fragmented marketplace, the biggest retail brands are the ones struggling to find growth. Instead, growth is being fostered by innovation from small to mid-sized brands — the companies who are able to follow consumer trends more quickly and innovate more rapidly and are more agile.”
This challenge for big box retailers goes back to the love/hate relationship with data — many are just beginning to realize that big data is not necessarily better data. Thanks to the collaboration between global data providers and technologies that clean, analyze and produce digestible data interpretations, larger retail companies now have the opportunity to take advantage of immediate access to real-time consumer insights and innovate. Morley continues, “while traditional analytics can guide effective long-term planning decisions, they must be fresh enough for teams to adjust to new threats in the moment. Data can enable collaboration if it’s harnessed in the right way and in the right hands. To do that, we must make the analytics typically saved for long-term strategic planning, more accessible for daily use by the everyday decision-makers in your company.”
Another challenge that is keeping retail executives and marketers up at night: keeping up with digital disruptions like Amazon. In order to survive, retail companies need to understand consumer preferences and behaviors around innovative retail tactics. Looking at the disruptions fueling Amazon’s growth and success, for example, retailers can identify opportunities to enhance their own models. A retailer might consider an automatic replenishing model for frequently purchased goods, for example - and this kind of decision should rely on accurate and complete consumer data. What makes sense for one group of consumers or markets does not always make sense for others, which is why it is critical to monitor and identify consumer trends at the granular level.
The Future of Understanding Consumer Behavior
The combination of a company’s own consumer data and independent big data sets are increasingly being leveraged for more personalized consumer insights. Retailers have tons of data from their POS, e-Commerce and rewards systems, but what they are missing is access to information about what consumers are doing when they are not in the store or on the website. It is the science behind connecting all of the external information with internal data together that makes it possible to pinpoint trends and completely understand consumer behavior.
The most valuable kinds of consumer data to collect largely focuses on geography, based on constantly changing, varying consumer tastes within markets. And just as technology has largely been a supporting factor for companies to gather consumer data in developing markets, it will continue offering new ways for consumers to shop and engage. And since there’s no existing data feed to sign up for as an easy fix, retailers should also think about emerging channels and how they can gather consumer information. For example, money-transfer options are expanding into mobile messaging applications and social media channels, meaning that digital shopping will is not far behind. While online retail websites are certainly a primary source of buyer behavior data currently, retailers will have to find new ways, like mobile receipt capture, to source data as consumers adopt other emerging shopping channels.
In order to keep up with the pace of changing consumer preferences, retail companies can no longer depend on what worked for them in the past to result in success in the future. As datasets grow larger, the use of data science and technology becomes a massive part of the challenge – but also poses the solution. With the ability to accurately predict the products consumers want, their preferred pricing points and their likelihood to purchase, retail companies will finally have the opportunity to use consumer data in their everyday decisions.
About Rich Wagner, President and CEO at Prevedere
With an extensive background in IT strategy and innovation, Rich Wagner has seen first-hand the power that external big data can bring to a company's financial performance. Today, as president and chief executive officer at Prevedere, Rich helps industry-leading companies like RaceTrac Petroleum, Masonite and Brown-Forman to look beyond their own walls for key external drivers of financial performance. He has uniquely positioned Prevedere as a complementary solution to existing forecasting platforms by tying the right external economic factors to corporate performance. Combining the power of big data, machine learning and predictive analytics, Prevedere drives unprecedented forecast accuracy. Under Rich's leadership, Prevedere has been named a "Cool Vendor in Information Innovation" by Gartner and an FP&A Innovation Awards winner in Forecasting and Planning. To learn more, visit www.prevedere.com.