First Published: 25 July, 2019
For most, the phrase ‘data analytics’ doesn’t immediately bring to mind ideas of doubling profit, or increasing marketing ROI by 30%, or finally outperforming competitors - but based on the challenges our clients have been able to solve through the use of their data, we think it should! Analytics isn’t about spreadsheets and number crunching. It’s about figuring out what business problem is keeping you up at night and pulling insights out of your data that will enable you to solve it.
Not convinced? Here are some great examples of pressing revenue challenges that can be solved through analytics.
Despite the growing prevalence of online shopping today, catalogue deliveries are still a significant sales driver for many retailers – particularly around holidays and seasonal changes. One of our large retail clients found that their catalogue distribution wasn’t delivering the results the business needed, primarily because it wasn’t well-targeted or personalised. As the retailer was preparing to launch its new season’s stock, the marketing team wanted to know where specifically (and to whom) it should be distributing the catalogues in order to get the best ROI.
Datamine analysed the retailer’s transactions and BI data and discovered that 80% of the households that were delivered catalogues generated 93% of the in-store spend, meaning the other 20% of the households only generated 7% of the spend. As a result of this analysis, catalogue delivery walks were ranked, and ‘hot spots’ and ‘not spots’ were identified to create a new master list for future catalogue distributions. This change delivered a direct cost saving to the retailer without adversely impacting its sales - more specifically, the new season period saw a 31% lift in sales over the same period the previous year, which was an excellent result considering wider retail spend during the period was down across the board.
Revenue issues are common amongst organisations of all industries and sizes, and one of our clients, a large international entertainment business, was facing a major year-on-year revenue decline from their loyalty base and didn’t know why. Despite the business having significant internal analytics capacity, they were unable to come up with an effective answer and therefore contracted Datamine to examine the problem.
We pulled thousands of variables and performed a comprehensive data mining exercise, ultimately pinpointing that the problems were due to several seemingly benign strategic changes in product mix, promotions, staffing levels, and pricing. Having identified the specific issues, Datamine worked with the business to plan and execute a revised strategy which reversed the decline - the $60k project delivered the business a net revenue gain of several million dollars over the following six months.
One of Datamine’s clients had an extensive customer base and a large amount of valuable data. However, they struggled to market to high-value customers because the records were housed in disparate systems, making them difficult to access and leverage for marketing analysis. To address this issue, Datamine created a Datamart (essentially a subset of an overall data warehouse) which tied all the customer information together and provided a strong platform from which to drive targeted communications.
The retailer’s $150k investment was recouped easily by the uplift in sales on the very first day the Datamart was used for targeting. In conjunction with additional analytics and capability supplied by Datamine to bolster the internal marketing team, this Datamart has subsequently delivered well beyond the client’s expectations, generating tens of millions of dollars of extra sales.
Turns out what you don’t know can hurt you. One of our large retail clients believed that out-of-stock issues were potentially having an effect on sales, but since that lost revenue was difficult to quantify, they weren’t able to justify additional investment into distribution. The company had tried and failed to perform these analytics using supply-side information, so they asked Datamine to examine the problem.
By using demand-side analytics, we were able to provide a good estimation of the cost of out-of-stocks at both a product and store level. This not only helped with the investment decision but also highlighted some significant disparities in operational effectiveness between stores. The results of these two insights were seen quickly as the $80k analytics job rapidly delivered a net benefit of several hundred thousand dollars per week by improving stock availability and out-of-stock processes.
These are only a few of the many examples of work Datamine has done to help businesses push the needle and increase profits. Check out our dozens of case studies to see what kind of work we’ve done in your industry, or get in touch with us explaining your biggest business challenge - chances are we can help!
Blog provided by Datamine
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