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KREATO CRM BLOG

AI for CRM & Sales – A Primer

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What is Artificial Intelligence (AI)?

Artificial intelligence (AI) is having computer systems to think and perform intelligent tasks like humans such as reasoning, discovering meaning, learning from past experience and understanding language. In other words we can say an AI system or product performs cognitive tasks that previously could only be done by humans.

Every business can improve their CRM and sales strategy by implementing artificial intelligence (AI).

Why You Need AI for CRM & Sales?

Traditional CRM platform are no longer enough to be competitive and successful. AI integrated sales CRM platform helps the organization to achieve greater sales goals – increase in lead conversion, increase in sales productivity and increase in sales win rate.

The major role of AI in sales is to augment the capabilities of sales team, empower them to understand customers, work more productively and achieve better results.

The sales CRM platform when powered with AI techniques auto drives team to adapt successful process for each deal, focus on what’s most important and perform right sales activities at right time in right way.

Introduction to AI Techniques

Popular AI techniques used in sales and CRM platforms are:

Machine Learning

With wealth of data on sales and customers captured in the system, your CRM has all the potential to deliver more value. Having the structured data is important but that doesn’t necessarily mean better decision making.

Here comes in Machine learning, the core driver of AI which keeps learning from your CRM big data and brings out intelligent insights to assist or enhance human decision making.

Ranking of leads by profile and behavior to prioritize leads on sales readiness is one good example of machine learning.

Natural Language Processing

Natural language processing is an effective application of machine learning, enables the system to find patterns in big data including unstructured data like email text, response templates or meeting notes.

One best application of NLP is interpreting incoming emails to categorize them by intent, identify emails that needs to be replied and auto draft the response.

Predictive Analytics

Advanced analytics technique used to make predictions about future events, based on patterns in historical data.

A practical application of predictive analytics is finding the optimal time to engage customer and the best channel to engage customer (when & where customer responds well).