Book Demo
Sales Software
Sales Enablement
Sales Efficiency
Customer Satisfaction

Integrating AI in Sales for consistent Customer Experience

Neil Sarkar,
6 mins read
Last updated:
Copy link

In the sales industry, performance optimization and achieving goals are constant, and here is where AI and ML come into play. You may program the system using machine learning to carry out particular tasks and achieve particular objectives. The same system can be made to repeatedly provide the same results by feeding it new data over time. With each iteration, the system can learn more about what works and what doesn't. This effectively means that AI can examine the data of prospects, forecast which of them will go on to the closing phases of the sales pipeline, and suggest the most effective course of action at each step.

According to analysts, technology has the potential to add between 1.4 and 2.6 trillion dollars' worth of value to the marketing and sales industries because of AI's capacity to increase and improve sales figures. AI technology is not a toy. The experiments, which have received overwhelmingly positive reviews, demonstrate that artificial intelligence may revolutionize society as electricity did around a century ago.

By 2030, the GDP is projected to expand by $13 trillion, according to McKinsey research. Curiously, a sizable portion of this development is anticipated in industries other than the internet, such as manufacturing, education, agriculture, logistics, and energy. These numbers ought to be the right motivation for you to create your own AI plan as a sales manager.

How can AI help in Sales?

As McKinsey research shows, companies that have pioneered the use of AI in sales have seen benefits, including an increase in leads and appointments of more than 50%, cost reductions of 40% to 60%, and call time reductions of 60% to 70%. Here are four important ways AI and machine learning can transform sales:

Lead Generation and Scoring

The skill of selling can occasionally be hit or miss. Sales representatives may spend ages attempting to close deals with leads with little interest in your goods and services. When this occurs, it isn't usually because the salespeople aren't good at closing deals.

According to data in the B2B sector, 61 percent of marketing teams often pass leads on to salespeople. Only 27% of the leads from this number are typically qualified.

This makes it clear that approximately 75% of the leads are a waste of time. Sales reps frequently cling to thin air since there is a lack of sufficient pertinent information about leads. It's difficult for businesses to impact the market without a strong understanding of the market and their customers. However, the dynamics can alter with data. Your efforts in this regard shouldn't stop at gathering personal information on prospects and clients. Data processing, with the aid of AI software, enables sales professionals to make decisions because of the technology's lead scoring feature. Overall, this data-driven strategy increases effectiveness and enables sales teams to engage in the traditional "willing-buyer, willing-seller" relationship. Since the AI algorithms are updated automatically whenever new customers make purchases, it learns more about the degree of compatibility over time. With the system continually running, you may obtain more precise results, and your sales force will spend less time thinking about whether their strategies are effective.


Because AI combines a good customer experience with precise targeting, selling is more straightforward than conventional techniques. Once you can tailor the content and the experience to the users in your database, this makes for a reasonably strong pitch.

As the numbers show, more than 50% of consumers are willing to share their data provided they can see content that aligns with their interests.

Given that AI systems can assess information such as preferences, surfing history, interests, and demographics, this specific statistic is not all that shocking. It's crucial to imagine how AI will change how you sell things as you consider implementing it in your system. By doing this, you'll have time to consider what to put up for sale and what other data you can feed the algorithm to help it do a more than admirable job of bringing in the correct customers.

Communication with Prospects

It is better to entrust chatbots with the task of connecting with customers in real time because they are equipped with the AI fuel of natural language processing. If you give chatbots these duties, you'll see that some of the Frequently Asked Questions (FAQs) can be answered quickly. Human interaction will inevitably be required sometimes; therefore, remember to account for that in your estimates. Ensuring a sales representative is knowledgeable about a prospect's demands before engaging them is critical in this situation. It's important to note that AI-assisted communication goes far beyond chatbots. You can decide when to contact prospects at their most receptive by using AI algorithms. You can build up a trigger-based technique that detects when a website visitor begins researching a specific line of products to get started. Your sales representatives can quickly jump in once a dialogue has been started, and the interest has been determined. Sales representatives can be more prepared in their manner of approach, the tone they use, and the language they use when speaking with prospects with the correct kind of data.

Boosting Sales Reps Efficiency

You can set up an artificial intelligence (AI) system that simplifies your manufacturing line and automates workflow instead of relying on sales representatives' abilities to "just wing it. "Delegation of tasks and priority will be automated in this fashion depending on various criteria. Because AI can identify the most promising prospects and assign the most acceptable sales representative who can contact them immediately, it effectively increases the effectiveness of your sales representatives. Here, the analytical component of AI systems is vitally important since it can determine which techniques are practical and which should be discarded. As a member of the decision-making hierarchy, you'll see that you can gather trustworthy information on the best course of action and choose which ones should be applied universally.

Challenges With Implementing AI and its solutions

Although AI-enabled solutions are becoming widely accepted, enterprises still face difficulties deploying them. The following are possible locations for roadblocks to appear:

  • Data:
    Data is the energy source for AI and ML systems. Businesses should ensure they have access to suitable data sources to get a complete picture of their consumers. The pursuit of flawless data availability, however, can sometimes provide challenges. Working with specialized data subsets for modest process goals can be a helpful first step when combined with initiatives to enhance data collection and quality.

  • Processes:
    It's crucial for sales teams to build data-driven processes and break down silos between departments that interact with customers. Vendors of AI-enabled platforms can offer the infrastructure and advisory skills necessary for such alignment and behavior transformation. While investigating viable solutions, organizations should prioritize simplicity of integration and uptake. Additionally, they should spend money on the training sales teams require to adjust to more data-driven, AI-enabled procedures.

  • Management:
    Successful AI/ML implementation can be significantly hampered by a limited budget and a lack of executive support. Building demonstrable use cases is vital to persuade doubters within the organization. Starting with a carefully thought-out pilot that shows quantifiable advantages can go a long way toward gaining support and funding.

  • People:
    Fears of job loss and redundancy always accompany discussions of artificial intelligence. Even in cases where these worries are unfounded, sales teams may be reluctant to make significant process changes. To overcome these challenges, decision-making processes must be open and inclusive, and sales reps must be provided with the tools they need to adjust to their new positions.

AI-Enabled Sales is already a Reality!!

It's not a far-off dream; currently, highly efficient sales processes supported by AI and machine learning techniques exist. Intelligent, integrated AI-enabled sales solutions may enhance decision-making, raise sales representatives' productivity, and enhance sales processes' effectiveness to deliver an exceptional client experience.

Suggested Reads