How to Get the Right Data for Machine Learning and AI

by | Mar 7, 2019

By combining end-customer data, marketing technology, machine learning and AI applications, businesses can deliver content and experiences to the right customers and decision influencers. The result: closing sales faster. This isn’t a fantasy. Storing the right data in the right place, allows a properly designed and configured intelligent application to access information and take action. Let’s get started!

1. Get More Of The Right Data

The best way to get more of the right data is to pull data from more sources early in the customer journey. Spend more time learning how your customers search for solutions, get buy in from decision-makers, and push through purchase decisions. This information helps you understand the content and experiences customers expect when buying your product. You can also get more of the right data by solving a critical post-purchase problem. Retention and customer growth are a challenge for most B2B companies, with the average B2B company retaining only 20% of customers. Think about making it easier for buyers to receive training, find the right tooling and resources, or run validation tests. Providing these services through connected devices, such as mobile apps or IoT devices, allows you to properly track and store the data you need.

2. Put The Data In The Right Place

Many companies have data living in many different places. But if you want to close sales faster, an API (Application Programming Interface) or similar service can extract data from one source and put it into your CRM platform. Today, over 80% of B2B companies have a CRM platform, but most aren’t used effectively or lack data, resulting in lack of use. Automating the data flowing into your CRM and using its alert and trigger features will close the gap between information availability and taking action on that data.

3. Continuously Learn From The Data

Machine learning and AI applications do a fantastic job of producing better and better recommendations, predictions and automated responses over time. A good example is lead scoring in a CRM. Today, the Salesforce AI application called Genius uses CRM Data to assign values to a prospect’s sales-funnel activities. As Genius learns, the scoring updates automatically, increasing accuracy and ensuring that sales agents are following up on higher-quality, read-to-buy leads.

Businesses in manufacturing, technology and consumer brands are starting to use machine learning and AI applications. But not enough are gathering the right data to increase value generated through the sales funnel. By using a connected device to address a major post-purchase customer challenge, you get the content and data you need to efficiently reach more high-value customers and increase the value of sales funnel activities through retention.

Want to learn more about shortening your sales cycles by marrying sales and marketing data with machine learning and AI?

Tessa Burg, VP of UX & Technology Strategy

From startups to global corporations, Tessa’s done it all. She applies her vast UX and technology experience to develop marketing plans that convert leads to sales.

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