Top 4 Sales Intelligence Trends from an Engineering Leader

2023 wasn’t just another lap around the track for the technology sector; it was a quantum leap into the future.

More specifically, we saw the pervasive influence of AI and how it reshapes every single focus area for sales leaders – including processes, people, and productivity. In fact, Goldman Sachs has predicted that generative AI will contribute to a staggering 7% surge in global GDP over the next decade and a 1.5 percentage point uptick in productivity growth. Anticipating this transformative impact, a projected 35% of chief revenue officers will resource a centralized “GenAI Operations” team as part of their go-to-market organization by 2025.

So, how will 2024 reshape the sales industry, and what trends should industry leaders be aware of? Here's my perspective as an engineering leader at Salesforce:

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1. Using gamification as a learning tool

Since its inception in 2008, gamification has become a popular strategy in the sales landscape. By applying game elements — like contests, badges, points systems, and leaderboards — into the sales process, sellers can transform tedious tasks into more dynamic and rewarding experiences. Gamification can also motivate sales agents to achieve individual or team sales targets; in fact, studies have found that nearly 90% of employees feel gamification leads to enhanced efficiency.

By using gamified training modules that mimic real-life discussions, we can enable our sellers to finetune their skills and refine their approach. (Of course, I have to give a shout-out to Salesforce’s own gamified learning platform: Trailhead.)

Picture this: we create an immersive scenario where a seller has to sell ‘Product A’ to a potential buyer. They are then given situations where unexpected turns in a conversation occur, and they must make decisions and select responses 00 and can also compare their responses to those of a star seller! Through this interactive approach, we can offer a practical and engaging method to enhance effective seller approaches and revenue-generating behaviours.

However, like with all technology, it's important we design systems that avoid biases. Acknowledging and comprehending diverse cultural, gender, and societal nuances and recognising their impact on consumer behaviours and sales approaches is critical.

2. Transforming generative AI into a virtual sales assistant

We all agree that sales reps thrive on relationship building and problem-solving — so how can we keep their focus there, instead of administrative tasks? In the coming year, we are going to see generative AI step in to provide intelligent support to sellers, letting them focus on what truly matters. Within five years, 60% of sales tasks are expected to be automated by generative AI technologies. In fact, Salesforce’s Generative AI Snapshot Research has identified three areas where sales professionals are most likely to use generative AI: 1) basic content creation; 2) Analysing market data; and 3) Automating personalised sales communications.)

• Creating content: In sales, generative AI can help craft personalised emails by pulling customers’ CRM data, past interactions, and product demos they've watched. Using advanced natural language processing, generative AI tools can also generate sales materials to address concerns for specific customers and accounts— even create slide decks relevant to opportunity stages in a deals pipeline! We are also going to see an explosion of generative AI-enabled chatbots across industries, which will help enhance customer engagement by providing better, nuanced interactions.
• Closing deals faster: Generative AI can analyse diverse interactions, generate cues based on successful past responses, and even flag ineffective practices. It can swiftly process vast amounts of customer data, including website behaviour, demographics, and purchase history — and then use this information to assist in Top of The Funnel guidance, or suggest the next best action to close the deal. While predictive AI has helped with lead scoring for quite some time, generative AI has a deeper contextual understanding that enables it to literally be your virtual assistant.
• Supercharging productivity: While AI tools have already made life simpler for sales professionals, generative AI elevates this automation by tailoring outreach and offers to resonate with each customer’s specific pain points and buying journey. Imagine an assistant that summarizes your calls, guides on meeting follow up, prepares your decks for your next customer interaction, even generates sales plays for you and trains you to sell most efficiently - all this is the power of Gen AI.

However, any AI model’s efficacy depends on the quality of training data. The issue of hallucination for generative AI means human intervention is needed, especially to take action on incorrect or misleading outcomes. This is important because the technology is still in its evolutionary stages, and we need to ensure human oversight till we are confident about reliable outcomes.

3. Strengthening predictive AI with generative AI

The synergy between predictive and generative AI will become essential as we move forward. Predictive AI uses historical data and statistical modeling to anticipate future behaviours and demand. Generative AI can play a complementary role and help derive value from structured and unstructured data. It can help craft fresh content by studying existing data patterns, foster creativity, and suggest innovative solutions.

For example, generative AI can create innovative designs for future products, while predictive AI can help forecast market response or customer demand for these features. Similarly, generative AI can act as a safeguard at a time when we are mining more and more relationships and social data for predictive insights. Its ability to anonymise sensitive data creates realistic synthetic datasets that can train predictive tools while safeguarding privacy, compliance, and ethical considerations.

4. Sales Analytics: Diagnostic to Predictive to Prescriptive

Future analytics in sales will prioritise proactive insights over raw data presentation.

Imagine a platform that intuitively reveals a seller’s performance projections without them having to ask questions. It proactively sends sellers tailored messages such as: “Based on current signals, there is only a 60% chance of you meeting your quota for the quarter. Here are five tailored strategies you can employ to correct this.”

Of course, for such a tool to produce maximum results, sellers at all levels must have access to relevant data and analytics.

At Salesforce, we are leveraging the capabilities of Data Cloud combined with Tableau, enabling automated actionable insights for various departments, including Sales.

I have observed one crucial element that can make or break the success of such an actionable platform for Sales Analytics; feedback. Feedback loops are important to ensure the efficacy of these insights in aiding sellers. By making continuous improvements based on seller feedback, such platforms can play a pivotal role in making the product better and shaping a company's success.

In 2024, the sales landscape is poised for another thrilling year of transformation. We've glimpsed the immense potential of AI, and now it's time to harness its power to empower — not replace — the human touch. As we step into this human-AI future, let's focus on ethical considerations, continuous learning, and feedback-driven optimisation. Together, we can unlock the full potential of AI and build even more effective, empathetic, and human-centric sales experiences.