Predictive AI: How to Use AI To Power Your Sales Efforts

Predictive AI: How to Use AI To Power Your Sales Efforts

Artificial Intelligence has slowly made its way into our daily lives, whether discussing self-driving cars, recommender tools, or complex predictive and personalized marketing and sales forecasting tools. ChatGPT also plays a huge role in driving the large-scale adoption of AI.

However, a few questions still linger:

  • How can you effectively use predictive AI within business operations?
  • How do you incorporate such technologies into your sales reps’ daily operations
  • Are there any tangible benefits of this technology when leveraged by sales departments?

To answer these questions, we need to set the stage: predictive AI can’t do the selling for you. However, it does provide solid insights to your reps so that they can increase their overall performance.

How Does Predictive AI Work in Selling?

In sales, Predictive AI uses historical data, patterns, and even external sources to forecast and enable businesses to make better sales decisions. By applying predictive algorithms to a company’s CRM or ERP data, sales teams can cut through the noise and automate much of the sales process, allowing reps to focus on nurturing and closing deals.

5 Ways to Leverage AI in Sales

Since AI has started to be incorporated into many business operations, you might have guessed that there are multiple ways in which you can use it in sales, too. Below is just a short list of those.

1. Lead Prioritization

Predictive sales AI analyzes your CRM data and factors like company size, industry, job title, etc., and generates possible outcomes based on historical data. Predictive lead scoring focuses on flagging the accounts’ conversion likelihood based on both internal and external factors and allows sales representatives to focus their efforts on those accounts that are more likely to convert.

2. Improve Retention Rates

Tools with predictive AI integrated are also great at monitoring customer activity and suggesting the next steps your reps can take to improve customer retention rates. You can leverage predictive analytics to assess customer satisfaction and sentiment detection, helping you to quickly identify which accounts are likely to churn. This enables sales reps to take preventive action and turn the scenario to the company’s advantage. Applying predictive algorithms to historical data gives you deeper insight into converting more cross-sell and up-sell opportunities.

3. Spot Key Purchase Influencers

Predictive AI can also help sales reps accurately identify which relationships and conversations are likely to influence a buyer’s purchase decision. More than this, Sales AI can also predict the number of interactions that are necessary with an account required to close a deal based on historical sales data.

4. Create and Improve Marketing Initiatives

Predictive analytics can be used to spot conversion opportunities before they even enter the funnel as prospects. When leveraged, it can help you identify high-potential prospects based on previous successful interactions and hand them over to sales immediately. Lead interest analysis allows you to create dynamic, multi-phase, highly targeted campaigns that drive more high quality leads into your pipeline. You can send more personalized email communications that drive deeper engagement and eventual conversion with sales and marketing AI.

5. Design and Launch New Products, Initiatives, or Services

Leveraged correctly, AI can help companies make better decisions, including launching products, services, or initiatives, based on past launches and external data, like market analysis. Used correctly, you can decide how to tailor branding, audience segmentation, manufacturing decisions, and logistics strategies.

Predictive Sales AI: The Benefits

Sales teams can benefit from predictive AI in several ways:

  • Reduces the risk of human error in the sales process
  • AI enables sales reps to make sense of the data they have at hand and eliminates guesswork
  • AI empowers sales reps to accurately predict sales patterns and the probability of closing a deal
  • Accurate lead generation and scoring
  • Boost customer lifetime value
  • Boosts sales forecasting accuracy
  • Tailor customer-focused marketing content and campaigns
  • Enables sales teams to address specific business goals and issues, such as accelerating business growth, improving CX, and building lasting customer relationships.

Predictive AI: Benefits for Customers

Because we live fast-paced lifestyles, we also request speed regarding business interactions. This is where predictive AI can come and help you deliver the right level of customer service your audience desires. With the help of predictive analytics, both sales and support teams can be one step ahead of their customers (and competition) by accurately predicting their needs and next steps that might work best in different settings and scenarios. AI enables you to serve viable leads faster while spending less time on false alarms. AI can monitor customer sentiment proactively identifying issues before they escalate.

Overall, AI gives you more time to focus on human relationships and value-added tasks with more precision and know-how.

The Future of Sales: Data-Driven, Predictive Systems, and Tools

AI has proven time and time again that it can intervene and facilitate processes where humans are prone to making mistakes. Simply put, it is a more accurate way of selling. No matter your organization’s size or industry, predictive sales software will help you work smarter, turn data into valuable insights, focus on key accounts and influencers, and increase speed to value – all of which to reach new levels of business performance and fuel growth.

Interested in learning more about Predictive sales analytics? Get in touch with us! We have hands-on experience and plenty of insights to share!

This blog post is based on an article initially published on Martech Zone.

Zac Sprackett
Zac Sprackett As Chief Technology Officer, Zac leads SugarCRM’s globally distributed product management, user experience, and engineering organizations. He is responsible for defining the product vision and strategy of the Sugar platform and for the execution of that strategy. He has over 25 years of experience in technology companies having held a variety of leadership roles. Previously, Zac served as Senior Vice President of Product, where he drove the strategic vision for the Sugar platform. Before SugarCRM, Zac held management positions at Geeknet, Mitel, VA Linux Systems and Corel Computer Corp.

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