During the course of 2020, rapid shifts in customer channel preferences, supply chains, distribution networks and ways of working created extremely testing conditions for the retail sector. The impact of the pandemic was the last straw for many retailers, who could not withstand the economic pressure of the changing market conditions.
For the retailers that survived, digital channels quickly became the key lifelines to provide business continuity and ultimately grow customer relationships. As customers migrated online, businesses that were already prepared for a significant shift to digital benefited from their position.
As retailers reshape their business strategies for 2021/2022 and beyond, it’s clear that new ways of thinking about customer data and developing new data capabilities will feature heavily on retailers’ strategic roadmaps.
Confidence in customer data will drive business valuation and improve compliance
Being able to unify customer data collected across multiple channels and systems, and build insights and intelligence across large and disparate data sets is becoming a foundational capability to maintain and grow business value.
Why is this important? One key contributor to business valuation is customer lifetime value and goodwill (or engagement), and investors are looking to invest in businesses that are using their customer data strategically. At the same time, compliance legislation is increasingly focusing on brands’ abilities to manage and protect their customer’s data and personal information.
As customer data becomes front and centre to business strategy and ultimately business value, retailers need to show boards and investment groups that they have a high degree of confidence in the ways they are managing, protecting and building value from their customer data. Retailers need to bring together customer profile data with digital engagement data and transactional data to build a total 360 view of the customer, across all their interactions.
Retailers that adopt intelligent customer data platforms (CDPs) can create operational efficiencies, deliver better personalisation at scale, improve their advertising effectiveness and improve their customer loyalty and lifetime value.
Compliance is also a key challenge for retailers today. Responding to compliance challenges is costly, time consuming and diverts focus from activities that grow revenue and improve profitability. Without a customer data platform the risk of duplicate identities makes it hard for retailers to really understand how many customers they have, what their shopping and communication preferences are and how they have interacted with the brand at every touchpoint.
Personalisation and marketing automation will take centre-stage
With the consumer shift to digital, retailers need to accelerate their personalisation and marketing automation programmes to keep pace with consumer expectations. One of the impacts of the shift to digital is that it’s no longer so easy for local retailers to differentiate themselves by physical experiences or face-to-face contact.
It can be easy for customer relationships to become very transactional with little opportunity to build a relationship. Understanding customer journeys across all the different touchpoints is key to building trust and engagement with your customers. Results from the recent Acquia Customer Experience (CX) Trends Report across Australia and Singapore shows us that brands think that consumers trust them with their data significantly more than they actually do.
Using technology, customer experiences can be personalised at scale based on data like previous customer interactions, product holdings, stage in customer lifecycle and engagement levels with content and campaigns. Without a unified customer view, poorly informed personalisation can actually detract from the customer experience and erode customer trust and confidence.
Marketing automation platforms enable retailers to build customer engagement at scale by automating customer journeys based on segmentation, events and customer interaction data, but without a solid customer data foundation, both personalisation and marketing automation programmes run the risk of delivering irrelevant content to the customer.
Decision making teams across all retail functions need direct real-time access to customer data and insights
With business landscapes evolving so rapidly, any bottlenecks in using data to make well-informed decisions is even more costly.
Direct access to unified customer data is becoming a must-have for all functional areas of the business. For example, finance teams need to understand which stores they should reopen, when, once social distancing restrictions are lifted. Service agents need visibility of customer interactions across every touchpoint, and the data to inform next best actions and product recommendations to drive cross-sell / up-sell revenue.
By enabling every part of the business with access to unified customer data, customer data platforms empower decision makers with a reliable and accurate source of truth combined with advanced analytics, dashboards and machine learning capabilities.
Real time integrations with analytics, websites, social media and mobile apps, marketing automation, personalisation, CRM and other customer engagement platforms ensures that customer data is up-to-date and ready to provide value.
Predictive marketing will help retailers address margin pressure and grow customer lifetime value
As consumers shift to digital channels, one of the risks for local brands is that their local physical locations are no longer a differentiator in a global digital marketplace. This creates pressure on margins as consumers are no longer prepared to pay a premium for a branded experience in a physical store or the convenience of leaving the shop with their goods immediately.
Predictive analytics uses machine learning to help provide retailers with the confidence to understand what is likely to resonate with customers. Predictive analytics helps drive revenue and margin by enabling retailers to identify and target customers that share similar characteristics with their best customers.
Machine learning and predictive analytics can help retailers understand a customer’s likelihood to buy, likelihood to convert or likelihood to engage. Retailers can then target their marketing budgets more effectively and improve their campaign investment.
To learn how retailers can use a CDP to shape their future roadmap, get the CDP Institute’s whitepaper: Customer Data Platforms Use Cases for Retail.