How to boost sales using predictive analytics
10/06/2021 - Pricing strategy
Predictive analytics is the study of results obtained through statistical methods and techniques that allow you to predict future situations. This, a priori, may seem complicated, but the truth is that it has excellent benefits for your business. Using predictive analytics, you can optimise performance, sell more, and achieve higher profits by anticipating your potential consumers’ actions and influencing them. Would you like to know how to sell more using predictive analytics?
5 steps to boost sales using predictive analytics
- Create product recommendations for customer groups. The purchase history of your repeat customers is only a bit away from your business intelligence. Leverage all of your customer behaviour information to offer related products and new recommendations with a guaranteed higher success rate. You will increase the value of your customers’ life-cycle, average ticket, and of course, seize the buying opportunity before your competition.
- Optimise your campaign prices. Predictive analytics is an essential component of price intelligence and dynamic pricing strategies. How? Using data obtained from previous campaigns and tracking the competition, it is possible to pinpoint patterns that allow you to have the best prices ready for the next event. You will maximise sales at peak demand and stay competitive when the forecast is not so rosy. An example of this is Reactev’s pricing simulation software. This solution allows you to make a detailed and realistic forecast of your pricing strategy, according to data collected from market performance in previous seasons.
- Segment your customers according to their online behaviour. Knowing your users’ activity allows you to assign them a value based on their likelihood of buying. It creates groups according to this probability, to manage concrete actions, which are individually targeted and offer them exactly what they need. It studies what products they look at, how frequently and at what specific times they are more likely to buy, the key values for this predictive analytics application.
- Make troughs in demand a thing of the past. With knowledge of fluctuations in the market, it is possible to know beforehand the times when lower sales are expected, and then establish specific campaigns to promote them. In this case, we would be trying to change the behaviour of the market, reversing the trend by marketing force.
- Stay in control of your inventory. Avoid stockout in your e-commerce with sales forecasts that show the results of the analytics. Seasonality and demand volumes should alert you to the quantity of product you need to have available to cover the orders placed with your business.
Personalise the user experience with predictive analytics
The path that predictive analytics follows in digital businesses is exactly the same one followed by user-centric data. Big data techniques already allow you to extract incredibly detailed data regarding your potential customers, be it demographic (age, origin or gender), or behaviour (interests, time spent using online platforms, profiles followed on social media...). And this is the key that today allows you to offer a personalised user experience, being ever closer to the ad-hoc offer.
Digital users receive thousands of hits every day, most of which they ignore, at least consciously. That is why it is so crucial for your business to be in the right place at the right time.
Thanks to predictive analytics, you can offer the best products for their needs, through the most relevant channels, and with the best prices according to the point they are at on their customer journey. Do you need more reasons to implement predictive analytics?
Category: Pricing strategy
