Customer relationship management systems have been around since Tom Siebel created one while working at Oracle in the late ‘80s and then monetized it founding Siebel Systems that eventually was bought by Oracle. When Salesforce launched its “No Software” slogan in the early 2000s, CRM moved to the cloud, but the concept was still based on a object model centered around an opportunity that represented a potential sale. The user interface allowed entry of data to the opportunity, along with various ways to report on the data.
Over the years, usability has improved the management of accounts, opportunities and contacts. The software typically includes analytics, digital experiences, enhanced third party connectors, workflow and task orchestration. Reporting is more robust. Going beyond sales, vendors offer support in the form of service tasks or case management. Most applications include some form of demand generation and lead management capabilities with the promise of connecting lead to opportunity to customer records.
When it comes to support for actually selling, CRMs have somewhat fallen short. Interestingly, the lack of real help for sellers or their management resulted in opportunities for start-ups offering add-on products to fill the sales engagement gap. One of the earliest examples is best classified as dialers or cadence platforms targeted at inside sales and sales development representatives with a defined structure or cadence to the activities. This includes so-called conversational analytics, where this analysis is used as part of sales coaching to improve individual performance and identify which messages resonate, and which don’t.
The second category is more focused on field sales and management. These particular add-on applications offer opportunity pipeline management views aligned with different reporting hierarchies that are ranked or scored using machine learning based on what a successful sale historically looks like versus unsuccessful opportunities. In addition, this pipeline view is used as the basis for judgment-based, bottom-up sales forecasting. But most CRM vendors are yet to have an integrated what we call sales performance management to ensure management and operations can manage sales teams.
One more specialized area that has seen recent development activity from third party vendors is in the area of date entry. It is ironic that many of the newer CRM are dependent on the timely and accurate collection of data while many CRMs have clunky and not user-friendly manual data entry capabilities. This has given rise to additional products that simplify data entry for sales teams by limiting visibility to only needed fields.
Overall, these complementary applications represent a small segment of the CRM ecosystem but nevertheless a significant market where traditional CRM vendors are viewed as ineffective. We believe that general
Over time, the scope of the CRM systems has expanded to include service and support, coupled with the rise of digital commerce and integration with finance, human resources, manufacturing, fulfillment and delivery. Organizations have looked for enhanced, low-cost integrations and the ability to automate processes across departments and teams to improve the customer experience. Vendors have also responded with low-code and no-code orchestration and workflows, plus more productized integration, and connection capabilities.
But CRM vendors are not blind to what is happening. Many large vendors have accelerated the development of pipeline and opportunity-management functionality. Applications to enhance sales forecasting incorporate machine language-based predictive scoring to complement opportunity-based sales forecasting. These systems also can aid in revenue forecasting by capturing non-opportunity tracked sales, deals not yet in the pipeline, and can utilize historical data to better predict product and service mix. Some vendors add dialers and cadence-based playbooks to support the inside sales teams. Automatic capture of calls, meetings and messages from common personal productivity tools improves ease of use and ensures timely and accurate data collection.
More recently, vendors have increased their focus on functionality that improves the buying experience, aids sellers in suggesting next best action and in navigating the buying organization. In addition, vendors are making better use of data to deliver personalized metrics and self-learning skill improvement. I believe these developments coupled with the adoption of generative artificial intelligence – point to the future evolution of CRM and the first true innovation since its inception some 20-plus years ago.
In a previous analyst perspective, I explored the role generative AI could play in improving many aspects of sales and marketing. As with the first AI wave for sales in the mid-2010s, the benefits identified in today’s use cases are, at best, incremental and, if deployed by all, will level the playing field rather than revolutionize sales. Many of these use cases are associated with productivity enhancements such as meeting notes summarization. None of these benefits change how the CRM supports sales. Any organization considering how generative AI could make a positive difference should ensure that vendors clearly articulate how AI helps sellers or provides some competitive differentiation. Validate this information internally to determine the difference these use cases might make.
What could the next generation of CRM systems look like? An interesting opportunity is the intersection of the digitally collaborative buying and selling experiences. Today, we have internal digital systems, but upon a buyer/seller interaction, the process reverts to analog and asynchronous. The distinction between CRM for sales and sales engagement applications will decrease as sales engagement systems expand to manage necessary master data – perhaps by synching with product information systems and customer and account master systems or managing the data directly.
Likewise, CRM systems will continue to add sales engagement functionality and, if innovative, will develop a truly next-generation engagement platform offering digital collaboration across revenue teams, prospects and customers. Some vendors have already introduced collaborative configure, price and quote features, while others have digital mutual action plans between buyers and sellers. Pricing guardrails at the point of sale have proposed pricing linked to commission projections and guidance on approval chances to influence discounts. Smarter tools are showing potential competitive pricing guidance as well.
With more commerce moving to a digital, omnichannel engagement, I see greater involvement of generative AI – not just to improve outreach or emails, but as discovery tools to better match buyers’ needs with sellers’ offerings. In industries using technical demonstrations as a proof point of the sales process, generative and predictive AI could bring a more automated and focused initial engagement. Support could include self-assessments pointing to a focused and tailored message or discovery answers to those engaged with the prospect. I envision this as a product-led growth engagement platform, with product instrumentation accompanying “try and buy” or other variations such as freemiums. For more complex sales, a generative AI-led approach can improve on the mechanistic approach of today’s CPQ products that depend on picking items from lists with preset rules around allowable, configurable combinations.
Many have written and will continue to write about the role of generative AI in outbound marketing and sales outreach. But these are not game-changing innovations; they are productivity improvements on current motions and will not compensate for uncompetitive products, pricing or service. Organizations should set expectations accordingly and challenge vendors to define how CRM sales systems deliver real and sustained benefit for buyers and sellers, not just incremental productivity improvements. There is nothing wrong with an incremental improvement unless it is sold as a revolutionary “game changer.”
Regards,
Stephen Hurrell