Three businesses where data drives decision making
More businesses are drawing on the power of data and analytics to help make better decisions and save costs, boost sales and increase margin.
Here are recent examples of our work across three different industries.
Real-time sales data
We have been working to provide real-time sales data to a manufacturer and wholesaler of diet supplements and beauty products with markets across Australia and Asia.
The issue for the business was that they were getting the previous month’s sale data midway through the next month and it was far too late to identify and fix any problems.
By contrast, we knew if we could provide real time data early during the month, they will have the opportunity to get any weak sales back on track and hit the month’s targets.
We built an interactive dashboard using Microsoft’s Power BI data applications to reveal the sales, order, and inventory holdings as they happen. The dashboard provides an overall view, showing daily company sales and margins for the month so far.
But what makes it a powerful tool is its ability to highlight granular data. From the consolidated view, uses can drill down into many different aspects of the company’s sales.
They can look at how volumes, prices and margins across different regions; different product categories and specific individual products; and individual customers, such as a pharmacy chain for instance.
They can also look at the last seven days of data and compare it to previous periods, or look at year to date, the last several years or really any period they choose.
The dashboard puts the data in the hands of the executives who need it, revealing to them where any sales or margin weaknesses are occurring and giving them the chance to take timely corrective action.
Reducing churn
We’ve also been working with a software-as-a-service business help them improve sales by drawing on insights from its customer subscription data.
It had two issues – unexpected cancellations from customers and customers who were only subscribing to a small subset of the SaaS services.
We started by taking historical data dating back several years to pinpoint the common characteristics of customers who cancelled their subscription. Next, we built a churn prediction engine by using the data to identify present customers with the same characteristics.
This gave the SaaS company’s account directors the chance to approach those clients most likely to cancel their subscription and see if the company had other offerings that would suit it better.
The company offers a range of products to customers, but most were just subscribing to one or two products from the basic offering while some customers were subscribing to a suite of the company’s products.
Once again, we looked across their customer base to identify the characteristics of customers who subscribed to several products. Then we identified customers which had the same characteristics but only took a small number of services.
It gave the sales team valuable leads for discussions about taking more services.
Taking the guesswork out of wine buying
A lot of people enjoy wine, but don’t know much about it and aren’t confident about buying wines they’ll enjoy.
Everyone’s wine tastes are different and we think a wine recommendation engine can help ensure that consumers buy wines they’re likely to enjoy.
We start with a wine tasting, collecting detailed consumers’ feedback on different wines – what are the elements of each wine they liked and didn’t like? We overlay that with demographic information about the consumer and build up a wine preference profile for each person.
We can see what other drinkers in that profile have also enjoyed and can then recommend wines that we can say with a high level of confidence that the consumer will enjoy – similar to Spotify with music or Netflix with movies.
By taking the guesswork out of buying wine, we can help retailers and wine producers make better recommendations to their customers and so keep them coming back. The tool can also help the retailer upsell a customer, say from two bottles to a half dozen, confident in the knowledge that the customer will be happy.