Machine Learning

Salesforce automation systems and broadly Customer Relationship Management systems have become indispensable for effective tracking on sales teams. Every sales organization has one, and every sales professional logs the activity into it (or at least they’re expected to). Now, logging is a passive activity that involves painstaking effort and discipline on part of the professional, but a data log by itself does not generate any additional value to its creator. Until now, CRMs have mainly served as databases. They don’t do anything to actually help reps perform at a higher level. Let's discover how to use machine learning to improve sales and roi.

Making sales teams productive is about making the data, which they put their time and effort into creating, also work for them. “Data is the new oil, but it’s only useful when it can be used to fuel intelligent algorithms” that augment human intelligence – popularly now known as Data Science. In the past decade, we have witnessed an increasing number of companies embrace big data and adopt  data science as part of their product offerings – Google search results, Netflix movie recommendations, Amazon retail recommendations, Paypal fraud detection algorithms, Facebook friend recommendations, Linkedin Job matching and many more. This has almost always resulted in improved user experience, increased sales and customer quality and satisfaction.

CRMs often sit at the heart of a company’s data assets have only gotten started with big data and are yet to realize the full potential of data science. Data science for Sales in broad strokes is about collection of various data sources related to CRMs (Big Data), applying advanced data munging (Data Mining) to connect the dots, leveraging rigorous science (Machine Learning) to extract advanced insights (Prescriptive Analytics) and build models that predict a future state (Predictive Analytics). The resulting data products have a single goal – making all the stakeholders in a Sales organization more productive.

Let us look at some of the possibilities that data science can enable for sales organizations.

‍Sales Representatives

Organize – Data can help organize the next set of opportunities to focus on that may increase chances of meeting his/her quota. Algorithms can also assist in research and communication with a lead/prospect and plan timely follow-ups – that can turn a lost opportunity into a potential one.

‍Decide – Algorithms can help sales reps decide between which product to suggest to the potential customer or what discount percentages would increase likelihood of a sale – and doing in real-time while still on that call.

‍Act – Data can suggest not only the best opportunities to work on, but the next set of actions to take that improve the conversion rates – akin to a turn-by-turn GPS for sales professionals.

Sales Managers

Optimize – Where is the next 10% improvement in revenue coming from? This is a question that’s on every manager’s mind. Does it involve re-assessing the performance of lead-sources, or re-arranging work loads of the reps? Whatever your strategy is, data can help, with consistency.

‍Drive Insights – Guide your team with data supported insights and not just by gut feel or even worse, none.

‍Visibility – Data collected about activity of the representatives at various granularities can bring much needed visibility into their performance and intelligence can then alert  managers to take charge at the right moments to save that $$$ deal.

Sales Executives

Forecast – If there is one thing sales executives care more than a healthy sales revenue, it is an accurate forecast of the sales revenue. Data collected automatically on how deals are progressing in the sales pipeline can be used to forecast revenues in a consistent and less complex manner. Also, unlike humans, robust algorithms are objective.

We at Predera work on artificial intelligence solutions that can boost your CRM and help your sales process deliver on the ROI promise. Drop us a note on hello@predera.com and we can talk.