Making great commercial decisions is hard. Especially amidst the cost of living crisis, ongoing supply chain issues and a rapidly changing retail market.
Decision intelligence is the commercial application of data science and AI. It helps business users make better, faster and more unified decisions – driving profits, reducing operating costs and increasing customer loyalty.
But how can you get started with decision intelligence as a retailer or brand?
Strong foundations are the key to long-term success.
Think of decision intelligence like building a house. Before you can start making physical progress by building the walls (ie making decisions), you need to start with strong foundations.
Affinity analytics, attributes, customer need states and segments are the cornerstones of great commercial decisions.
Put together, affinity analytics, attributes, customer need states and segments create the foundations for true decision intelligence. Each piece of foundational insight is interlinked. Building it layer by layer creates sophistication and drives more intelligent decision making.
Affinity analytics creates the foundations for customer need states. Attributes explain in detail what those need states are, and segments bring everything back to the customer level, either on a macro, micro or individual level.
In action, affinity analytics could find six pairs of women’s branded white trainers at a high-end price within a retailer’s range. The customer need state could be defined as ‘luxury white trainers for women’. In this case, the attributes could be ‘luxury footwear’, ‘expensive’ and ‘branded’. A micro segment could capture all shoppers interested in expensive footwear, with a propensity for buying branded products.
So, why’s this important? Retailers and brands can use this information to personalise customer experiences. After all, personalisation improves customer experiences and boosts loyalty.
Layering the building blocks.
Affinity analytics, attributes, customer need states and segments are also the building blocks for personalisation. 71% of consumers expect personalised experiences, so they’re an essential part of brands’ business strategies.
These building blocks can be layered to build transformational insights across the business:
Retailers can use customer need states to establish how many products serve the same need. Any unprofitable lines which don’t serve a unique need but have obvious substitutions can be removed from a range. Affinity analytics also helps predict demand transference.
The endless aisle can lead to eternal scrolling – and no one wants that. Retailers can use customer need states to reimagine their merchandising hierarchy. They can also create curated ranges, providing shoppers with relevant, frictionless experiences.
Pricing and promotion.
Customer need states help retailers understand promotional cannibalisation. Meanwhile, affinity analytics helps optimise different price points within a need state. Using data (rather than gut feel) to find the optimal price point drives customer engagement.
Marketing and media.
Affinity analytics, attributes and customer need states work together to surface personalised recommendations for customers. Segments help create micro or individual lists to send relevant marketing communications that drive genuine engagement.
After offering personalised ranges, retailers need to be able to fulfil orders and delight customers. Supply chain forecasts can be carried out at customer need state level – any products in a need state are substitutes for each other and share a demand profile.
Putting data at the heart of decision making.
Ultimately, data is key.
Without a data-driven culture, businesses will never be truly customer-led. They risk making misguided commercial decisions. They risk delivering poor customer experiences. At worst, they risk obsolescence.
To create decision intelligence, retailers must place customer and product data at the heart of their decision making. After all, great commercial decisions help brands compete – and succeed.
Our decision intelligence platform is now available. The first module helps create deep customer insight, including affinity, attributes, customer need states and segments. Armed with this insight, retailers can make key marketing decisions to drive revenue and loyalty.