Predictive Analytics have become the “big thing” in the retail industry and I agree, they can be an important and powerful tool for brands and retailers. Why? First of all, they enable commerce organizations to work in a more efficient way in every area of their business and second of all, they improve the quality of their decision-making processes.
Benefits of Predictive Analytics
Especially the potential for efficiency improvement makes predictive analytics so interesting and valuable for the retail business. Time is money in today’s competitive environment – so there is a legitimate reason to deal with this subject.
Analytics and analyzing data sets or rather looking for specific patterns within the data often results in time-consuming and in some cases repetitive tasks. With the use of predictive analytics, patterns within the data can be identified automatically and there is no need for employees of the commerce organization to search for them manually. All the analytical effort can be focuses on understanding the patterns and translating them into action.
And even with that, predictive analytics can provide a boost for an efficient working environment: Employees of commerce organizations are provided with far easier access to the findings of the analyzed data sets. Predictive analytics facilitate findings in a way that makes it easier for everyone in the company to understand what the data shows – no need to be a data scientist or a statistics expert anymore to actually make use of the data and reach operational excellence.
Why Predictive Analytics are no Panacea Though
But there is a big “But” – predictive analytics are able to solve several problems, but they’re not a panacea. They are a great tool for commerce organizations to improve certain processes, but it would be too easy to think that a “machine” can always make the best business decisions.
And here’s why: Predictive analytics are only as good as the data they work with. And that is usually the key aspect in which brands and retailers have a lot of catching-up to do. Especially when it comes to linking customers with their full touchpoint history – not just online, but also in the physical store environment, in the call center and more – into a logical and comprehensive data warehouse. Creating the source data pool predictive analytics can rely on is the key to unlock the great potential of this tool.
A Solution for Salesforce Companies
Also in the Salesforce eco-system, we see that Salesforce retailers struggle heavily with that challenge. They’re simply lacking a solution that helps them get those basics right before they should even think about predictive analytics. And as Salesforce itself doesn’t come with a solution for this and companies usually don’t have the necessary knowledge in-house, they’re depending on solution providers specialized on Salesforce companies who help them out.
At this point, minubo enters the game. minubo, certified Salesforce partner since 2014, creates a holistic omnichannel database and makes the data accessible for all user groups: Data from Salesforce, order management, webtracking as well as POS data is collected and integrated into a full omni-channel data warehouse according to the logic of a best practice commerce data model. Ultimately, it’s made available in an Analytics & Insights App comprising various data insights tools like a flexible customer segmentation, a web pivot and a proactive insights stream and, via a feed API, enables intelligent automation with direct connection e.g. to email marketing systems.
With that, minubo enables true data transparency and allows commerce organizations to be fast-paced and efficient in order to gain strategic and operational excellence. All in all, it actually offers crucial advantages in any business context: Mistakes are detected and can be eliminated, but also positive trends become visible and can be strengthened. These insights enable commerce organizations to recognize and capitalize on the full potential of their business model as well as to closely monitor the success of new strategies and processes – which in my opinion should be the key use case of any analytics project, may it wear the label “predictive” or not.
And actually, against this background, our analytics vision doesn’t wear a label like that at all – it’s focused on what we envision our customers to achieve with our solution, the minubo Commerce Intelligence Suite: We want to enable all teams within the commerce organization to make smart day-to-day decisions relying on one holistic database. In short, we put our vision into one simple term: data democracy!
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