Predictive Analytics

Predictive Analytics is used by companies to predict future events. The process typically includes analyzing historic data they collect and creating machine learning techniques combine with a variety of statistical algorithms.  

Companies can use predictive analytics to:

·      Help improve the accuracy of forecasted revenue. For example, Microsoft IT is using predictive analytics – built on Azure Machine Learning and open source technologies to help the sales team to better predict sales. According to Microsoft, “they incorporated a predictive analytics tool in opportunity management in Microsoft Dynamic CRM Online. This model uses machine-learning algorithms and opportunity-scoring data for near real time win/loss predictions of a sale. It helps sellers prioritize by showing whether an opportunity is hot, warm, or cold, and advises them about actions to take.“¹

·      Optimize marketing campaigns. By collecting customers’ behavior data for key learnings (such as what products they tend to purchase, what marketing campaigns they tend to respond, which are loyal customers and how did they get to that point) predictive analytics can determine which of these characteristics combine and correlate to turn a prospect into a customer. Predictive analytics helps companies to determine which marketing campaigns they should employ next as well as to help them attract, retain and grow their most valuable customers.

·      Improve their product recommendation techniques – determine what product their customers are more likely to buy next based on his/her purchase history and then recommend that product. For example, if a customer bought a ski jacket you might recommend ski goggles.  As another example, if you notice that a customer bought facial moisturizer and you can offer similar moisturizer of a different brand that is highly rated you might suggest it to your customer. These strategies provide a personalized customer experience and should result in increased sales. Amazon is a great example of a company that successfully utilizes product recommendation techniques. “The company reported a 29% sales increase to $12.83 billion during its second fiscal quarter, up from $9.9 billion during the same time last year. A lot of that growth arguably has to do with the way Amazon has integrated recommendations into nearly every part of the purchasing process from product discovery to checkout”. ²

·      Determine price strategy. Predictive analytics helps companies to determine the right price for a specific product or service by analyzing historic data about sales, customers and other product specific metrics. There are different factors that help each system to determine the right price for a product.  Some examples include demand for a product and how much it is affected by competitive prices, seasonality (some products have stronger sales in the summer, therefore there is more price elasticity in the summer season), store capacity, weather patterns and much more.

·      Better manage the supply chain. By collecting information about customer demand, predictive analytics can help businesses to better manage their supply chain process and optimize the use of available warehouse space while minimizing the likeliness of out of stock items. “Large retailers are realizing the benefits of predictive analytics for supply chain management, as evidenced by Walmart’s recent acquisition of Inkiru, a predictive analytics startup with models for supply chain optimization.”³

·      Detect Fraud. Cybersecurity is a big issue that a lot of business are suffering from and trying to prevent. By utilizing a verity of predictive analytics tools you will be able to collect and store historical data that will also include past fraudulent transactions. When combined with rich transactional data sets and combined with 3^rd party data, analytical tools can help detect and prevent fraudulent transactions by running verification algorithms, in real time and prior to the completion of each customers purchase.

Sources:

1. https://www.microsoft.com/itshowcase/Article/Content/770/Predictive-analytics-improves-the-accuracy-of-forecasted-sales-revenue

2.  http://fortune.com/2012/07/30/amazons-recommendation-secret/

3. http://www.practicalecommerce.com/6-Benefits-of-Predictive-Analytics-for-Online-Retailers