Question Clearly sourced

Expert knowledge for digital decisions

What Does AI Really Bring to a CRM?

Short answer

AI is useful where unstructured text is processed: categorizing emails and assigning them to the right case, summarizing conversation notes, preparing response drafts. It is less useful for forecasts – most companies lack the data volume from which a model could reliably learn.

What Works Well

Categorizing Incoming Emails. To which customer, to which case, how urgent. Errors are cheap to correct.

Summarizing Notes. After a long conversation, three sentences with the essentials and the next step.

Response Drafts. Based on the history – one person approves.

Searching in Own Documents. "What did we offer this customer in 2023?"

What Rarely Delivers on Its Promises

Closing Forecasts. A model needs many examples to learn. With two hundred deals a year, the data volume is too small – the prediction is hardly better than the weighted pipeline that does not require AI.

Automatic Evaluation of Contacts without verification. See lead scoring: The order may be determined by a system, but a rejection should not.

The Basic Rule

AI suggests, humans decide. A CRM that autonomously classifies customers, rejects them, or sets prices quickly violates Article 22 of the GDPR – and is also difficult to correct if it is wrong.

Data Protection

If customer data is transferred to a cloud model, this constitutes processing on behalf of a third party and requires a contract. For particularly sensitive data, an in-house model should be considered.

Honest Advice

Start with email categorization. It occurs most frequently, saves measurable time, and an error can be corrected in two seconds.

Key facts

Well Suited
Categorizing emails, summarizing notes
Overrated
Closing forecasts with small data volumes
Basic Rule
AI suggests, humans decide

Sources

All external claims are backed by traceable sources.
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