Integrating big data into CRM systems for smarter, faster and easier sales

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For sales teams, successful selling is all about capturing the maximum value for the goods and services you supply to customers. To do so you need to begin by understanding each customer's willingness to pay.

Ultimately the answer begins with one key question: What is the best way to gain this understanding and provide accurate price guidance so that sales teams can present the right offer? For many companies, it’s all about the Customer Relationship Management (CRM) software, that’s used by their sales teams. That said it has become apparent over the last few years that CRM alone is not sufficient, as it doesn’t capture customers’ willingness to pay.

This may explain the plethora of configuration, pricing and quoting tools on the market today. The fact remains that CRM screens are where sales teams spend a significant proportion of their working day. It is there, not in some other pricing tool, that they need to be able to access optimized price guidance for each customer. By aggregating data from multiple sources into the CRM system, companies can capture relevant information to help their sales team accurately price products and services from a single system. That’s the power of big data. Using big data – and applying data science – helps companies identify buying patterns and preferences. Sales teams get easier, faster, smarter price guidance about each customer or prospect directly from the CRM system.

So what sort of data should be integrated with your CRM system? The simple answer is ‘whatever data is relevant to your product lines, individual SKUs and offerings’. In some industries, it's easy to gain an understanding of competitor pricing simply by accessing publicly available data. Other external data sources such as commodity or input prices can vary frequently, even daily. In certain cases these sources may be highly relevant to your pricing decisions and how customers respond to your offers. By having the most current data in the price guidance system -- based on scientifically defined customer/product segments and willingness to pay -- your win rate will be significantly higher. Integration with your CRM system also means you are able to react faster to changes or market discontinuities that have a critical impact on the types of offers your sales teams should be making.

Let's look at two examples:

  • If a new market entrant has the potential to gain significant market share, you may well decide to respond by modifying your offer. Or you may wish to hold your prices constant, instead focusing on the value-added services you provide along with your product. But whatever you decide, your sales teams need to have this information. Price guidance therefore needs to appear in your CRM system when your sales team makes contact with customers.
  • External data sources may alert you that a competitor is running a particular sales promotion in one geographic area. If that's the case, you can flag this information for customers in that region so that sales staff can react accordingly, perhaps with specialized pricing or by increasing the richness of your offer.

So what sort price guidance should a sales team expect to find in its CRM system? Here are some examples:

  • Smarter quotes: If sales reps are quoting  a deal, willingness to pay information and current market conditions should be integrated with the contact records.
     
  • Optimized pricing: Pricing needs to be optimized for each customer based on willingness to pay and relevant external data. Are they looking for the best price or a more expensive package that also includes services? What offers are competitors making?
     
  • Built in CPQ: Where product offerings are more complex, configure-price-quote (CPQ) functionality should be embedded in the CRM software. This will enable sales people to configure bundles and packaged solutions, not just simple set of products, services or software, in order to optimize price quotes.

So, we know that using big data and applying data science to identify buying behavior can increase sales effectiveness. The degree to which this happens, however, depends on how well this insight integrates with the CRM systems being used by sales teams. Pricing guidance makes use of all relevant data sources, whether from CRM or other data-driven systems, which in turn means that sales teams are much better equipped to meet quotas and close those deals smarter, faster and easier.

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