See what happens when accurate foresight gets actioned
For Retail and Hospitality marketers, building customer loyalty, retention, brand reputation and awareness are all top of mind.
But gaining a better understanding of your brand’s perception through the lens of customer opinion, feelings and beliefs is challenging.
So, how do you better gauge brand sentiment through the voice of the customer?
Current analytics tools offer limited views on what’s being said about your brand, as they mainly focus on social media analysis and sample surveys.
They don’t show how you’re perceived through all online and offline touchpoints. So, you’re not getting the bigger picture.
Understanding your customers better is more important than ever. This means getting personalisation right. It really pays, especially when you’re creating customer experiences – so they’re aligned to their ‘actual’ wants and needs.
This means you’ll need more advanced data analytics designed by retail experts to equip retail professionals with the most accurate foresight so they take the most valuable future actions
This is where Predyktable comes in. We go way beyond just predictions. We create prescription models that predict what will happen and tell you what to do when it does. It’s what fuels our smart segmentation model.
The way we shop has never been more flexible, with purchases being made on multiple devices, browsers, and sessions. But the price of consumer convenience, is ever-increasing complexity for marketers.
Tracking the success of your marketing spend across individual channels and customer touch points is practically impossible. Any attribution of credit to a sale is now tenuous at best.
Dynamic Demand Forecasting
Every retailer understands the importance of having the right product, in the right place, at the right time.
In this climate of perpetual change, your stakes are high. So, how do you make profitable decisions through the lens of regional demand?
You need to dig deeper than just price. Your customers’ expectations are also driven by availability, experience, and ethical considerations.
And don’t just rely on historical data. It doesn’t provide enough information to make accurate forecasts. Decisions are just risky bets.