While retailers want to win with predictive analytics leveraging Big Data, consumer goods companies are gradually driving direct relationships with the consumers.
Deeper Data Collaboration is a Win-Win Agenda
Retailers and brands have traditionally shared information primarily around product and supply chain and mostly not in real time. The customer-related information is only limited to an aggregated demand signal, but there is an ever-increasing opportunity to share and collaborate on customer intent. Customer intent refers to the prepurchase journey in the search-discover-evaluate-purchase-engage value chain. The consumer data is collected by both retailers as well as brands from their respective owned and controlled channels, and this continues to increase with the proliferation of customer engagement channels. Winners are exploiting the opportunity to collaborate on improving upon a unified view of customer intent at different levels of granularity. Both retail businesses and brands can benefit even more from this. From a brand perspective, it needs to become easy to do business with (ETDBW), when it comes to enabling a retailer to provide a seamless and consistent experience. It's important to continuously enrich customer journeys with rich and relevant product information. While building this, considerations such as confidentiality contracts with the consumer and ecosystem participants need to be taken into account.
Creating a Collective View of the Consumer
Consumers used to get product information from advertisements and by talking to salespeople in brick-and-mortar stores. Today, shoppers aggressively research and compare products before setting foot inside a store. Or, even while in the store by looking across competitive retailer outlets on their smartphones and tablets. Due to the smartphone revolution, prices, product variations, and reviews are more available and easier to compare than ever.
This showrooming trend can result in lost customers and revenues. It also renders traditional approaches to collaboration between manufacturers and retailers ineffective. Making decisions based on historical sales data is no longer sufficient. Driving category growth is increasingly about serving the right information to the shopper at the right time to support a purchase decision.
What’s needed is cooperation along with analysis of integrated data to deliver actionable insights that enable better brand, product, packaging, supply chain, and business planning decisions; and to power shopper marketing programs in-store and online. This approach benefits not only manufacturers and retailers but also consumers who enjoy the advantages of shopper rewards and loyalty programs.
Data-Driven Collaboration to Influence Purchase Decisions
With many shopping decisions being made outside the store environment, there is an increased priority placed on understanding and influencing shopper behavior at many points along the path to purchase. Mobile, social networks, web, and e-mail channels are the new media used every day by marketers to target content and offers that drive purchase activity. One-on-one relationships are becoming the new currency upon which the most valued brands are based while creating unique shopper experiences have come to define retail excellence.
Leading CPG companies have differentiated themselves by executing laser-focused consumer connection strategies based on data analytics. A variety of data-driven decisions, from assortment and inventory planning through pricing and trade promotion, affect shopper purchase outcomes.
Based on integrated and detailed data, from sources such as the retailer’s point-of-sale system, loyalty programs, syndicated sources, and data aggregators, analytics allow CPG companies to become more relevant to their consumers by meeting their needs, earning their loyalty, and building relationships. In short, advanced analytics separate successful retail-CPG partnerships from those that aren’t.
Leveraging Shared Insights for Operational Synergies
Maintaining an efficient distribution and inventory process is critical to maximizing financial performance and meeting buyers’ expectations. Sharing shopper data and insights support concepts such as collaborative demand forecasting, dynamic replenishment, and vendor-managed inventory.
Price, promotion, and shelf placement are critical areas that drive collaboration, but the efforts are often based on summary-level and infrequently updated data. To effectively move the needle in managing a category at the shelf, organizations must have a strong data analytics foundation. Armed with better insights, category managers, store operations leaders, merchandise planners, and allocation decision-makers can optimize the factors that influence sales performance of products in specific categories, geographies, and stores.
Some Live Examples
Here are some examples of how some consumer brands are leading the way:-
- Anheuser-Busch created a balanced portfolio approach which guides retailers on how to maximize sales via an optimal product mix across the entire category. Anheuser-Busch even compensates some staffers on their retailers’ growth in the category, not limited to their own products.
- Kimberley-Clark has obtained a dual view by complementing weekly total sales data at the chain level derived via syndicated providers, with more granular real-time data provided by Food Lion. Using a web-based SaaS tool, Kimberley-Clark started with a retail performance scoreboard and drilled down within the harmonized granular data to mine for opportunities.
- Walmart’s retail link facilitates data sharing to empower suppliers; via the Inkiru acquisition, they can now enable real-time intelligence to predict better on-shelf availability.
- Lowes developed LowesLink, a platform that gives suppliers access to in-store transaction data allowing them to analyze cross-sells, geographic penetration, and orders to codevelop insights and strategies.
Creating Common Data and Analytics Platforms
CPG manufacturer and retail business executives must recognize the value of fact-based decision-making enabled by integrated data and real-time analytics. Data-driven collaboration establishes a beneficial connection that allows both sides to achieve common objectives, including increased product sales and growth in revenue. The benefits of digital collaboration go well beyond the bottom line — retailers and manufacturers can improve customer experience and shopper loyalty, reenergize their stores and brands, and generate customer enthusiasm for new products, amplifying sales and market share.
In fact, retail businesses and CPG companies are even sharing their data and analytics platforms to improve customer experience. The availability of data is enabling a new era of collaboration between them on their digital initiatives. The key to finding success lies in putting advanced analytics and insights at the core of the relationship, with a combined laser focus on understanding the customer.