Adobe and Publicis Sapient conducted a study to assess the current data maturity of top retailers and uncover gaps in their analytics strategies. The research explored executives’ perspectives and proficiencies in areas such as customer data platforms (CDP), artificial intelligence (AI), and algorithmic retailing. (See methodology section for details.)
As a new decade begins, our survey demonstrates the significant progress data analytics strategies have made over the past ten years. In 2010, Big Data was barely on the radar for most retailers; now, the conversation centers on how to harness data for maximum value to both customers and the business.
Large retailers are competing to get ahead of the data curve, but most are still using data and automation primarily for basic marketing tactics, such as detecting customer product preferences or predicting customer intent. Ironically, 60% of retailers surveyed feel they’re ahead of their competition on AI, but our findings show that it is still early days for data analytics and AI in retail. Many respondents have yet to fully leverage data to streamline business decisions and measure the link between customer experience and business value.
60% of retailers feel that they’re ahead of their competition on AI, but in reality, only pockets are actually ahead of the curve and many don’t understand what true data maturity looks like.
“Retailers create 40TB of data every hour, and that data is often hard to work with and often noisy,” said Hilding Anderson, Head of Retail Strategy, North America at Publicis Sapient. “Then the insight layers are overly simplistic and don’t use the latest in AI; they’re much closer to Excel spreadsheets. And on the action side, a lot of retailers don’t have an integrated tool set where they can action against data models that are creative. This takes time and investment, but our findings suggest that retailers are overconfident.”
Retailers use data to paint interesting portraits of consumer behavior and engage with them more effectively. For example, U.S. consumers spent $142.5 billion online during the 2019 holiday season, a 13.1% increase year-over-year, according to Adobe. Smartphones accounted for 84% of last holiday season’s e-commerce growth. During the holidays and throughout last year, many retailers’ data analytics strategies were tested as they competed with e-commerce giants like Amazon and implemented new privacy policies to comply with laws such as GDPR and the California Consumer Privacy Act.
Despite these challenges, there are myriad ways retailers could be more imaginative with their data, such as using it to detect life events, create customer genomes, or predict lifetime value.
Retailers create 40TB of data every hour, and that data is hard to work with and often noisy.
Experiences and events have become more important for many consumers than material possessions, but this isn’t doomsday for retailers. Brands can still anticipate these experiences and events to reach consumers when they’re planning for a wedding or the birth of a child.
“I would say we are farther away than we’d like and I think it’s because as soon as we get closer to it, the goal posts keep moving,” said one respondent from a big-box retailer. “The challenge is in the past when people would have said, ‘hey, we’re almost close to getting that single data lake,’ it’s more like, ‘well, we thought of about 17 more use cases so how’s that going.’”
Virtually all respondents are confident that investments in analytics drive business results. However, many retailers still need to go deeper to maximize the use of available analytics, such as minimizing returns, forecasting demand, and optimizing inventory. Only 29% said leveraging statistical models and techniques to minimize the number of returns describes their organizations very well, and 27% said using analytics on external and/or internal drivers of demand describes their organizations very well.
(Scale: 1 - Does not describe your organization at all; 5 - Describes your organization very well)
The AI skills gap has widened in recent years as the technology becomes more prevalent. The World Economic Forum estimates that 54% of the global workforce will require significant reskilling by 2022.
At some organizations, teams that should be in close communication do not or barely interact with each other. One respondent from the pet care industry said that their organization hasn’t yet “seamlessly integrated the insights and analytics team with the digital team in order to properly mine the data,” which remains one of the largest bottlenecks to enabling the full potential of their organization’s data.
The skills gap is impeding many organizations from using analytics to their full potential. According to our survey, 44% of respondents said shortage of AI skills is a top three challenge for why their organizations haven’t adopted the technology. Employee adoption of AI came in ahead of lack of skills, with 45% saying it’s a top three challenge.
Many retailers are talent-starved where data is concerned, and siloed investments in people, processes, and platforms are hurting their ability to train and hire talent that can take their analytics to the next level and keep pace with advances in AI.
“Organizations haven’t yet seamlessly integrated the insights and analytics team with the digital team in order to properly mine the data.” – Surveyed respondent from the pet care industry.
The good news is that more than half of respondents indicate their company is piloting or experimenting with the C-suite actions that are essential to avoid either excessive skepticism or unquestioning acceptance by employees or management. Machine learning algorithms can learn from data without specific rules, building models to make data-driven decisions or predictions rather than following strictly static program instructions.
Data shows that despite the difficulty of coordination, the ROI necessitates the approach for a single platform. For retailers that measure ROI on analytics and customer experience investments, one-fifth indicate a typical return of 31% to 40% on their customer experience investments. “It’s going to be tough for large retailers to build that connected single place because it’s just a lot of investment, a lot of teams have to coordinate,” said one big-box retailer. Nevertheless, the data shows that despite the difficulty of coordination, the payoff necessitates the approach for a single platform.
It’s helpful to think of the money-under-the-mattress analogy to picture how many retailers are currently approaching their analytics. Less than half of respondents are using their core data in ways that go beyond marketing, and this is keeping many consumers from having a truly relevant shopping experience.
Our respondents represent large companies that likely have many processes and policies in place that prevent them from being as nimble as smaller companies without legacy systems to replace.
No one said it would be easy for retailers to tackle data maturity. Organizations don’t have a choice but to use all the tools at their disposal to convince customers to give their loyalty to their organization instead of a competitor. But that’s still not the reality at many retailers, given the 60% of respondents who feel they’re ahead of the competition, when our work and knowledge of the retail landscape tell a different story.
Retail has always been competitive, but the pace of that competition has never been faster. Our global team of experts can help translate the confidence that many of our respondents felt in their analytics progress – and many were too confident – into a foundation that will enable you to keep pushing your data forward in ways that make customers fall more in love with their relationship to your brand.
The Adobe Retail study was completed via online interviews by a third-party research firm hired by Adobe and Publicis Sapient. The sample is comprised of 150 retail respondents. Interviews consisted of an administered questionnaire, covering the following topics:
The retail sub-segments include: Apparel, Grocery, Discount Mass Club, Consumer Electronics, Department Store, Health and Beauty, Home Improvement, and Specialty. The Adobe Retail study was conducted throughout October and November of 2019. The survey had 150 respondents from the US, Canada, France, Germany, and the UK. All survey respondents were actively employed by a retailer at the time of the study. All retail organizations surveyed have $2 billion+ in annual revenue.
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