Here are five ways that AI can practically support effective sales strategies for manufacturing, distribution, and wholesale enterprises in 2024 and beyond.
As we gear up for a technology-driven world, where we will see gigantic leaps in the applications of AI & ML technology – here are five ways in which we believe AI can practically support effective sales strategies for manufacturing, distribution, and wholesale enterprises in 2024 and beyond.
1. Reducing product and customer churn
2. Generating relevant and role-specific insight
With sales operations in busy enterprises often extending into the hundreds of personnel, getting a holistic view of how your overall sales strategy is performing is essential to driving bottom-line gains. AI applications will continue to take this to the next level by delivering rich, tailored sales insights to sales personnel at all levels within the enterprise—from target-driven sales professionals at the coal face to profit-incentivized directors in the boardroom.
Practically speaking, this means a sales manager having real-time analytics to know when individual personnel is under and over-performing, for example, and sales execs having detailed intelligence to indicate when a customer may be significantly dialing up or indeed reducing spend.
3. Driving supercharged customer intelligence
Building effective, trusted personal relationships with customers will always be a vital element of the role of any sales professional. With the proliferation of data in today’s enterprises, emerging AI applications are facilitating next-level customer insights that haven’t previously been possible through interpersonal relationships alone.
By effectively harvesting and amassing historical data on a range of customer relationships, the most forward-thinking sales teams are developing ‘super-intelligent’ customer profiling that can help identify multiple opportunities to do better business – from insight on when a sale might have been missed right through to when an upselling opportunity may crop up in future. The upshot is better, more informed customer conversations each and every time, and, ultimately, stronger customer relationships.
4. Finding the hidden patterns
Enterprises collect vast amounts of raw data across multiple data repositories. The actual business value of this raw data is only realized when this data is combined to establish patterns using such techniques as statistical analysis.
These patterns form key business insights that enable organizations to spot hidden informational trends and identify both outliers and key business drivers to enable more effective next-best action for sales recommendations.
5. Getting your team's game on
Driving employee satisfaction and motivation is one of the critical challenges of the age for enterprises looking to retain and, indeed, attract top talent. We already see the potential of AI applications to significantly assist in this process by adding gamification elements to everyday aspects of the sales role.
Leader boards, badges, points and scores, levels, and challenges are popular gaming elements we expect to become commonplace within sales operations in the new decade.
Retaining the human touch.
Of course, brilliant technical data solutions count for little without the touch of a skilled, physical salesperson to interpret the insights they deliver. It should be remembered that harnessing AI isn’t about replacing the sales role but rather equipping sales professionals with the right tools to sell smarter.
As such, the uniquely human aspects of the sales profession – such as the salesperson’s perception of a customer relationship or account, for example – will continue to be essential in feeding valuable knowledge and intuition into the process.
What’s more, human insight will be equally crucial in overseeing the design and efficacy of AI models to ensure they are fully explainable and have removed biases caused by any false assumptions made in the AI learning process.
Equally, human input will be required to ensure that models truly represent a specific organizational structure and size, considering industry or sub-industry verticals together with regional and geographic variances.
Optimizing the AI in sales-i.
Here at sales-i, we’re not just talking about AI like so many other commentators. Today, we’re actively working on several exciting AI-based applications to deliver these benefits to sales professionals. These new capabilities will feed into our AI-guided selling and sales enablement platform to provide more in-depth customer behavioral insights for proactive sales professionals, ensuring every conversation they have is insight-led and profitable.
About sales-i:
Transitioning from traditional business models to digital ones can be challenging for many organizations. They often struggle to maintain order volumes, meet sales targets, and stay updated with product trends. Identifying patterns in customer buying behavior is also a struggle, ultimately leading to declining sales. These challenges can make it harder for enterprises to achieve sales excellence.
sales-i provides customer data to reps in the simplest way possible, helping them easily read complex datasets, identify new opportunities, and have profitable conversations. Our platform is capable of recommending products based on historic purchase trends. You'll be alerted to changes in buying behavior and can prioritize customers who have stopped buying from you.
sales-i is one of the first sales intelligence platforms in the world to use artificial intelligence to produce insights at a product level. Our tool provides insights into product as well as customer data, including reps' performance. This helps sales managers identify top-performing products and missed opportunities for upselling and cross-selling.
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