❝Let us take you through the story of Reboot – a hypothetical shoe manufacturer and retailer, and their CEO’s experience with Salesforce CRM Analytics.❞
Reboot was started in 2015 as an initiative to reduce the waste generated in the fashion industry. Richa Singh, the CEO of Reboot patented a method to manufacture athletic shoes by reusing waste materials from other shoe and clothing manufacturers. Over the years, Reboot has become quite popular among a select niche of customers. In 2018, Reboot had implemented Salesforce CRM to keep track of its Sales and Service verticals.
Richa has been using Salesforce standard reports and dashboards to keep a track of important KPIs. But over the last few months, she has realized that the standard dashboards are not dynamic enough to help her in taking proactive decisions. Her business is increasing and it is becoming highly difficult to predict the shoe production volume every month. In the retail industry, demand depends on various factors and when her outlets report stock outages, customers become unhappy. Richa cannot afford to lose the customers she has gained over the years.
She is aware that only data analytics can help her make informed decisions. While searching for possible solutions, she comes across Salesforce CRM Analytics – a complete package of Visual, Predictive and Prescriptive analytics which requires no coding.
Features of Salesforce CRM Analytics
Reboot sells 4 types of shoes – Running Shoes, Court Shoes, Hiking Shoes, and Cross Trainers. The shoes are available for both men and women in multiple shoe sizes. Each shoe type has a different profit margin and separate set of raw material requirements. Richa wants to view the annual revenue and quantity sold till date. With these requirements, she approaches the Salesforce Implementation Partner, and she is blown away by the initial results.
Not only does the dashboard allow her to view the annual revenue, but she can also drill down from the dashboard using filters. She can get the revenue filtered based on product model, shoe sizes, gender, and date of sale. She can also slice the data based on the unit of products sold vs revenue generated. All of this can be achieved in a single interactive view without the need for multiple reports and dashboard components.
The Salesforce consultant also gives Richa a demo on how she can track the performance of her sales team. With the below dashboards, Richa can identify and reward her high performing Sales Executives. This will boost her sales and promote healthy competition among her Sales staff. Richa can also monitor her revenue stream from different sales channels and drill down to individual Sales Rep’s performance.
Now that Richa can efficiently track her revenue and motivate her sales team, she needs to focus on her next pressing challenge – how to prevent stock outages in her stores. Retail demand depends on several factors such as price of the product, customer’s taste and preferences, availability of substitutes, seasonality, etc. If Richa is not able to predict the demand for her shoes in time, she will not be able to procure the raw materials required.
When she approaches the Salesforce Consultant, she is amazed to hear that Salesforce CRM Analytics can also be used to build customized predictive models to forecast demand. The forecast algorithm can be tweaked as per the business requirement to achieve a high accuracy model, by taking into account all significant factors that impact the demand. And all of this can be achieved without the need for any coding!
Richa can also drill down and view the demand forecast of each model and each gender. This is awesome because model wise demand will help Richa streamline her procurement process.
Richa is so impressed by the Salesforce CRM Analytics functionalities that she is eager to understand how else this tool can be utilized to grow her business. The Salesforce consultant give her a few different ideas-
1) WhiteSpace Analysis
As Richa expands her business all over India, she can use whitespace analysis to understand the correlation between products and the customer demand based on region. This can show her useful insights which she can use to up-sell or cross-sell to her customers.
2) Targeted Marketing
By combining customer data with sales data and using Salesforce CRM Analytics, Richa can predict her product life cycle. She can use this data to send personalized targeted messages to potential customers before launch of new products. Targeted marketing can also be used to encourage existing customers to repurchase from Reboot.
3) Predict Customer Churn
Prescriptive models can be built in Salesforce CRM Analytics which predict customer churn and suggest best steps to prevent a customer from churning. Such models are custom built for every business and their accuracy can be increased by changing the predicting factors.
To summarize, Salesforce CRM Analytics is a powerful tool and has multiple applications in the retail industry. The dashboards are insightful and predictive models can be built without the need of complex codes. If your organization has already adopted Salesforce for its business processes, Salesforce CRM Analytics can provide an added edge to your business decisions.
Author: Shivangi Tiwari
Editor: Sohini Bose