SaaS Backups Can Power Big Data Insights for Retailers

No one likes paying for backup. Obviously, retailers need it. Businesses today operate on data, and without it, commerce grinds to a halt. But it’s painful to spend money on something that you hope you never have to use. The value is all tied up with the nasty what-if of corrupted data, a fire, a natural disaster, or a successful ransomware attack.

Although this is a common feeling about data protection, backups can provide value to an organization even if they aren’t used to recover data. And if a retailer is backing up its SaaS-based CRM (likely Salesforce), those backups can be especially valuable.

First, however, we need to talk briefly about why one needs to back up SaaS-based CRM platforms like Salesforce, because I’m certain some readers are thinking, “Why would I need to back up my Salesforce data? Doesn’t Salesforce do that?”

The vast majority of SaaS and cloud vendors, including Salesforce, operate on a shared responsibility model. This means that while SaaS vendors invest a lot of resources into ensuring that their infrastructure and software services are secure and well protected, the customer is ultimately responsible for their data.

If data is accidentally or maliciously deleted, without a separate backup, it’s likely gone forever. And if the SaaS vendor has an outage, without a backup, that data is inaccessible until the SaaS platform is back online. Given how much retailers depend on their CRM systems for day-to-day operations, it’s critical that they back up their SaaS CRM.

Now let’s discuss why these backups don’t just have to sit around like useless bumps on a log until the retailer needs to recover data. In an excellent case of “killing two birds with one stone,” modern extraction tools can pull data out of backups into a data lake, where it can then be used in an analytics framework.

The big data analytics and artificial intelligence systems that enable accurate answers and predictions have a tremendous appetite for data. And with so much data just sitting there, doing nothing, in backup files, they represent a treasure trove of raw material that these systems can transform into valuable business insights.

A modern retailer needs to be able to connect its supply chain to its sales operations, and connect the dots on how its marketing efforts directly or indirectly affect sales. By doing this, the retailer gains the ability to answer questions like the following:

• What are the most important current consumer trends for my business and what are their likely effects?
• How does the weather affect sales of specific goods and services?
• How should I prepare for public holidays to maximize sales and meet customer demand?

How would this work in a real world situation? One large retailer that implemented Salesforce and extracted data from backups into an intelligent engine wanted to determine how long it would take a frontline employee to stock something in a store before and after an intelligent workflow was implemented. Once the system ran the numbers, it determined that each frontline employee would be able to save three hours each week with an intelligent workflow. That may not sound like much, but with 25,000 employees accessing the system, that means the company would save 3.9 million worker hours each year, which at $20 per hour, translates to $78 million in savings annually.

That’s a lot of value from “useless” backup data. All organizations need to do is extract it for big data analytics.

Remy Claret is the co-founder and chief marketing officer at Odaseva, the leading enterprise data platform for Salesforce.