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How Exactly are Retailers Leveraging Customer Analytics in 2018?
What’s the secret to creating deeper customer engagements and more personalized experiences? Many would argue the golden nugget is found in data and analytics. On February 28, we hosted a roundtable at the Retail Hive event ‘Engaging the Connected Customer’ in London where more than 100 participants from leading retail and consumer products companies shared their experiences and challenges around this topic. Here’s a quick run-down of our roundtable discussions.
Availability of Customer Data – when it comes to having access to customer data within your organization, where do you currently stand?
The Hive community is diverse, so the range of responses came as no surprise. Everyone agreed that customer data tends to be scattered, captured across a series of front and back office retail processes, and held within multiple systems that are frequently disconnected. The more data-driven organizations have already begun to embark on significant investments in Data Lake or data warehouse solutions. For many though, tapping into a pool of data for valuable customer insights remains a distant aspiration.
Customer Analytics – how mature is your understanding of what your customers want and need?
Varying responses showed a divergence between businesses engaging directly and indirectly with the end consumer.
For organizations one step away from the end consumer, strategic investment in developing deep analytics capabilities supported by technology and people skills seemed more prevalent. One common initiative included building a set of consumer personas. Given the grey areas where 360 degree information about consumer behavior is missing and still has to be inferred, this approach is not free of challenges.
Many mature retailers seemed to be successful with Agile methodologies by pushing the customer analytics agenda forward within their organizations through trial and error, continuous improvement and a focus on demonstrating ROI from smaller analytics solution projects. Digital customer-facing platforms are an ideal vehicle for this, although heavy tagging across a site has at times led to performance issues, so the advice was to always balance business need with technical feasibility.
Could it be that this divergence between adopting a strategic (top-down) or a tactical (bottom-up) approach is related to the ownership of customer data within an organization? Responses from our roundtable participants indicated that there’s no ‘one size fits all’ solution when it comes to a successful customer analytics strategy, or even when it comes to identifying who within the C-suite is accountable for leading the customer analytics transformation agenda.
Advanced Technologies and Personalization – what is your appetite for using advanced technologies, such as machine learning, to personalize the customer experience and deepen customer engagement?
While there was a mix of responses from the group regarding more advanced tech, there were a few who had positive experiences to share.
One retailer shared how their company applied machine learning-powered chatbots to their eCommerce platform to filter simple customer queries, freeing up time for dedicated virtual agents to field more complex inquiries. This enabled a more personalized shopping experience for customers without adding headcount for agents.
A start-up business explained that they intend to move beyond simply collecting data on past customer interactions and develop a machine learning-enabled solution based on internal and external structured and unstructured data to personalize the products offered to individual customers. It’s interesting that a start-up could move so rapidly toward advanced technology, which prompted us to think that this may be a benefit of not being encumbered by legacy systems.
Our Roundtable Conclusion
We are encouraged to see a high level of interest surrounding customer analytics in 2018. The majority of retailers are still figuring out ‘how to get it right.’ For those who may already have invested in gathering reams of customer data, the problem of how to best draw valuable insights from it (to find those golden nuggets) remains unresolved. For those not yet off the starting block, driving the customer analytics agenda would be easier with a C-level advocate. But, practical examples show it is possible to gain influence and buy-in from the ground up – it’s all about building a community of advocates at every level in your organization.
Advice from EPAM – where to start on your customer analytics transformation journey?
Many companies may rush to focus on the immediate need for technology solutions to consolidate disparate data, but we would suggest pausing to first consider your strategic analytics transformation roadmap. As one of our clients said, “don’t fall into the trap of capturing or measuring for the sake of it, first be clear about what you are trying to measure and why.” It’s also important to view data in context, so having data science capabilities within your organization is also something to seriously consider in 2018.
As for the evolution of more advanced customer engagement technologies, let’s see what this year really delivers…
Justine Stanton is Director, Retail Consulting Services Europe at EPAM. She has 20+ years of experience working with global organizations across mass market, general merchandise, luxury goods and telco sectors.