If you’re a marketer in the retail space you’re likely to be hyper focused on precisely targeting your key demographics through data. I know you’re collecting data because, well, who doesn’t? Everyone is collecting data but the key is what do we do with the data?
Large retail companies, usually with over $1 billion in sales, are typically lucky enough to have a team of people analyzing their consumers’ purchase data and providing marketers with key information to help pinpoint specific groups with targeted marketing campaigns. But what if your company isn’t a large retailer?
What if you’re a small- to middle-sized retailer? You still have to handle your consumer data for best results. Fortunately, data analytics doesn’t have to be out of reach.
Consider these questions: How do you predict which customers will buy? And when? How much will your customers spend? What products will they buy?
Most data analytics that are used to answer these questions are looking backwards. HOWEVER, what isn’t done as frequently in the analytics world is predictive analytics. Looking forward. What if you used analytics to individually analyze every single customer? And then used probability to predict what they are more likely to buy? And then were able to target your marketing accordingly?
We have a way to solve that challenge: predictive customer intelligence based on customer buying behavior. Using past purchase history to predict lift in revenue, all through data science! What’s great for retailers who don’t have big budgets for analytics is that it’s actually surprisingly affordable for a company to analyze their data looking forward versus looking backwards.
Using data science, we can help retailers predict loyalty, risk, value and the product purchasing behaviors of each customer. You’ll be able to see what lifecycle stages your customers are in and understand from a 1:1 perspective, how to best market to each customer. Even better, the process is automated and you don’t have to be a data geek like me to understand the impact of the numbers.
Practically speaking, how does it work? Well, it’s easy to use and doesn’t actually require a lot of client data to be effective. We can help you take the data you currently have and find the best customers to target for your next campaign. Why waste money marketing to customers who aren’t going to purchase? Instead, we can tie these data analytics into a fully personalized print campaign. Using predictive intelligence in this way can lift results 10-30% or more.
Curious? Contact me and I’ll share some case studies with you.