Covering Disruptive Technology Powering Business in The Digital Age

Years ago, Albert Einstein purportedly set his students the same exam two years running, asserting, “Same questions, different answers this year.”

This makes many ponder if their sales function may be experiencing a similar phenomenon. We still need leads, engagement, discovery, conversion, and revenue, but the process has transformed. In a complex B2B environment, buying groups are growing, and buyers, armed with the information they researched, are spending just 17% of their purchase journey with potential suppliers!

Against this backdrop, sales teams need to maximise their assets to increase efficiency and effectiveness across every stage of their sales process. They should think about how and where to use data, apps, Artificial Intelligence (AI) and automation to help them get rid of busy work, fix broken processes, convert data into insights and prioritise their time for customers and prospects.

Presuming that salespeople split their time between primary selling (one-on-one communication with prospect and customer) and secondary selling (prospecting, writing proposals, administrative work and more), it can be a worry to learn that sales reps are spending only 54% of their time on primary selling, according to SugarCRM’s sales leadership survey.

This is why many businesses are now looking to adopt modern technology with the goal of reducing secondary sales friction and enhancing their sales process. To achieve the most success, sales reps should ideally be following the process that includes four stages: Find, Engage, Close, and Plan.

• Find – Prospecting Stage

Acquiring market databases that provide static data typically offers limited value. But intent data can offer insights into potential customers, their needs, and purchasing likelihood.

These data can come from CRM platforms or third-party applications like Bombora, Triblio, or Demandbase. They score intent activity within the CRM, notifying sales teams swiftly and efficiently.

Hyper-tuning the Ideal Customer Profile can enhance sales precision too. Additional techniques to capture intent data involve leveraging existing tools, such as reverse IP lookup, clickstream data, form conversion data, and email analytics. Blending such static and intent data can empower sales teams throughout their sales cycle.

• Engage – Communication Stage

Generative AI is transforming content creation, data analysis, and optimisation. The four use cases for generative AI in sales include nurturing content, conversational analytics, automation, and workload optimisation, as well as time planning and scheduling.

Sales teams can leverage AI to streamline communication, extract insights from conversations, automate processes, and enhance productivity. Integrating AI into the sales and CRM platform can eliminate duplication, optimise data entry, and use win-loss analysis for outcome prediction. Automated tools can assist with social media management, scheduling, workload optimisation and meeting organisation.

• Close – Knowledge Stage

In a sales process, 1:1 engagement is crucial, and leveraging AI and data optimisation can enhance efficiency.

While competitive intelligence can be transformed using generative AI, machine-learning, and natural language understanding, internal knowledge utilisation can also be streamlined using AI techniques like abstractive summarisation and topic detection. Integrating AI into sales processes and leveraging third-party apps for data discovery and collaboration can add value to your business.

By embracing AI and data optimisation, your sales teams will gain a competitive edge, adapt strategies accordingly, and deliver compelling proposals.

• Plan – Optimisation Stage

Forecasting used to be a one-dimensional model focusing on sales performance. This means that sales executives had limited visibility and control over forecast data from various sources.

To enable intelligent forecasts, sales teams should consider target verticals, buyer needs, historical patterns, content, and interactions throughout the sales process. AI and automation are, thus, crucial in this case due to the vast amount of data involved.

Integrating this capability into the sales and CRM platform is vital for optimal sales forecasting and planning.

As technology converges, AI and automation are fast becoming core components of CRM platforms. With a solid and open platform that can process both internal and external data, reduces workload, and enables automated forecasting, the foundation for success is laid.

AI-powered sales and CRM strategies can provide significant ROI through efficiency and effectiveness gains. In this new landscape, sales teams should be prepared to deliver different answers to the same enduring sales questions.

Watch this demo to find out more on how to leverage AI and take your sales and CRM efforts to the next level with SugarCRM. Alternatively, if you’re ready to find out more, reach out to schedule a demo or for further assistance.

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