CRM Made Smarter by Evolving from a System of Record to a System of Recommendation

January 14, 2020 | 4 minute read
Kamyar Seradjfar
VP Product Management, Oracle CX Sales
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It’s no secret that today’s customers want to make purchases any way they choose. They want choices that include price and product configurations, new buying models such as subscriptions, and prefer brands that know when to offer hands-on help, especially as digital and sales-assisted buying experiences continue to blend.

Great sales teams are advocates for their customers, and being a great advocate starts with getting better recommendations, not just better customer records, from your CRM. With a system of recommendation in place, sales teams can spend more time selling and less time preparing. When they can understand their buyers on a deeper, more meaningful level, they can work harder to cultivate a personalized buying experience that leaves customers happier and drives more revenue.

The Old CRM is a System of Record

To better understand their target buyers, sales teams have historically relied on customer relationship management (CRM) systems to hold data about prospects and customers. Integrations with other systems link other customer data such as marketing campaigns, service interactions, purchase behaviors, proposals, and more. When all key data is entered, cleaned and deduplicated, CRM acts as a powerful “system of record” that informs sales forecasting, commission modeling, outreach prioritization, and other areas of business.

However, for CRMs to be useful, they must have good data. This is easier said than done because, in reality, sales reps typically have to spend time manually entering data, a task which they hate! This means that data entry is often deprioritized, thus CRM data becomes stale and reps are less likely to use and update their CRM. When contacts are outdated, company profiles lack context, and pipeline/funnel data is incorrect, the value and influence of CRM plummets, and the vicious cycle compounds.

The New CRM is a System of Engagement and Recommendation

Today’s customer buying journeys are less formulaic, more complex, individualized, and curated. Therefore, sales reps don’t just need data; they need to be able to access and leverage incredibly timely and relevant insights that empower them to better sell and serve customers.

According to recent SiriusDecisions research, “Improving sales rep productivity must be an ongoing pursuit for sales operations, sales enablement and sales leaders. However, sales organizations should move beyond a focus on increasing activity (e.g. “sending more emails and making more phone calls”) and seek to add insight and intelligence to buyer and customer interactions (e.g. when to send, what to send, how to send, whom to send to).”

Enter the dream team

Data-fueled AI can introduce automation that minimizes the time sales reps waste on non-valuable tasks like documenting follow-up activities. It can automate manual tasks like data quality and enrichment and improve the data set that drives its very own effectiveness. The result is things like surfacing recommendations that resonate with customers at the exact moment they are most likely to engage with the brand.

Modern sales teams need a “system of recommendation.”

Meet The System of Recommendation

At Oracle, we apply a few key lenses to develop sales tech and applications that prioritize the needs of sales reps so that they can advocate for their customers.

  1. Rich data: Advanced CRM combines data from first, second, and third parties in order to create rich client and company profiles that support multiple areas of the business. Rich customer insights help sales better understand their prospects and customers and help colleagues in marketing, commerce, and service do the same. Rich data incorporates real-time signals about what’s happening for an individual, their organization, and their immediate world. Examples include knowing which trade shows that key customers and prospects will attend, technology they already own, and news announcements that indicate revenue growth or decline.
  2. Whole business revenue generation mindset: While CRM can integrate with other core business systems such as enterprise resource planning (ERP), a shared data model is even better when the entire business is engaged in generating revenue. With Oracle, customer data management (CDM) is the backbone of it all, providing a single point of truth about your customer. For example, consider how historical ERP and order data such as purchase history and renewal info can give a sales team insight to improve territory planning, individual rep incentives, and forecasting. This type of pre-planning and sales right-sizing provides a foundation on which marketing and account teams can plan, and for customer success teams to engage at the right time.
  3. User Experience: It’s widely agreed that for a CRM to be used, it must be easy to access, continuously updated, and optimized. It must offer a seamless experience on desktop or mobile. A true system of recommendation travels anywhere a rep goes, in a format that’s familiar, and arms them with insights on any channel as they engage with customers. Many core selling activities should be supported through voice and conversational UI. Smart and often simple UI changes can help create a faster path to that essential data and recommendations for sellers. Any element that can be automated, should be. Your CRM doesn’t need to look like a CRM.
  4. AI and Machine-Learning Recommendations: Powered by real-time continuously-updated data, artificial intelligence (AI) and machine learning capabilities are essential to providing a system of recommendation that helps sales close more business faster. These recommendations can range from surfacing the most relevant records at the most opportune moment to more advanced capabilities like next-best actions and win-probability calculations to help reps and managers proactively spot risk. The next wave of AI innovations will focus heavily on sentiment analysis and relationship intelligence, augmenting rich CRM data and surface new types of insights and recommendations that fine tune the selling process.

Pretty soon, you may not recognize your CRM. Sophisticated selling organizations are taking a closer look at how richer data, better automation (actual sales automation), revenue operations, machine learning, and major updates to user experience can give CRM a fresh new identity.

Click here to learn how Oracle can help you reimagine your CRM strategy for the Experience Economy.  





Kamyar Seradjfar

VP Product Management, Oracle CX Sales

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