The predictive value of analytics to increase sales

Why use predictive analytics in your business?

Predictive analytics helps you increase sales. That’s what makes this data technique the most effective weapon you can use in your business today.

Predictive analytics techniques use data obtained by very precise tools that detect market trends and behaviour patterns, both by your competitors and the consumers themselves. This means you can predict both peaks in demand and potential issues in the production chain, and even price changes for products in your catalogue. This is one of the main applications of predictive analytics: to fine-tune a dynamic pricing strategy to fit your needs, to allow you to sell more and better.

Today, according to a Spanish survey published by IT User, 79% of companies already use data analytics tools to extract market information, and apply it to their business strategies. Of its many advantages, they highlight a better understanding of consumers, the savings achieved in operations and logistics, and the increase in total sales. More than 40% of respondents recognised that their use of this data focuses on the sales and marketing side.

4 ways to implement predictive analytics to increase sales

Multiple sectors use predictive analytics, such as gambling, health, insurance and financial risk assessment. Collecting and analysing large data sets significantly reduces uncertainty about implementing new strategies.

There are many uses of predictive analytics. Here are four examples that you can apply to increase sales in your business.

1. Price strategy simulation. Reactev is a pioneer in offering a pricing strategy simulator that uses predictive analytics to test strategy viability and assess potential profits. Reactev is an essential tool if you wish to know in advance the effects and consequences of implementing a new strategy. Remember to run A/B tests at the outset that additionally provide you with ways to compare the two options.
2. Optimisation of promotions. In addition to simulating comprehensive pricing strategies, the software uses predictive analytics to provide information on viability of discounts, both from the actual sales probability, and the profits returned by a price tag. With promotion optimisation tools, you can find out the best discount to balance maximum sales with prices that will guarantee sufficient profits.
3. Improve your stock management. Each season, the demand for products and the price users are willing to pay for them vary. Analysing the number of references sold and consumers’ behaviour will allow you to translate this to your warehouse and avoid stockouts. It will also help avoid overstocked warehouses that only make you incur increased expenses. You can make the most of your sales capacity every season with predictive analytics.
4. User segmentation. The link between big data techniques and predictive analytics is unbreakable. That’s why the more you know about your users, the better the sales ratio you will achieve. How? It enables you to offer related products which are more likely to be bought based on purchase history. It also allows you to offer special discounts to consumer groups with common characteristics, whilst maintaining profit margins for your business.