Transform Your Marketing & Sales with Smart AI in Salesforce

We all feel that the potential of AI is huge, but practical adoption often still lags. Turning artificial intelligence into tools that deliver measurable business value is a common challenge.

Executive Snapshot: Turn AI hype into measurable Sales impact

‍Seeing AI potential is easy. Turning it into outcomes is harder. Get inspired by two real-world manufacturing use cases: faster quoting and AI-assisted self-service for customer order requests, enabled by Salesforce as the single source of truth and reliably connected to ERP.

[.infobox]Salesforce is a cloud-based CRM platform that helps companies manage customer relationships and accelerate sales and marketing by centralizing customer data in one place, automating key processes (such as campaigns, follow-ups, and pprovals), and providing insights and predictions through reports, dashboards, and AI[.infobox]

Real-world industrial AI that actually delivers: Faster quoting and automated customer requests

We’d like to share two AI use cases from manufacturing companies that are feasible — and, most importantly, already working in practice.

Use Case 1: Configuring the Offer

Imagine we are a manufacturing company, and we want to make life easier for our salespeople and technical specialists in the process of gathering customer requirements, configuring the right offer, and presenting that offer to the customer in the correct format.

In this case, the goal of using AI is to speed up the process and create space for salespeople so they can focus more on finding and acquiring new customers.

This process is a strong candidate for AI for several reasons. Many manufacturing companies generate a large part of their business from repeat customers, where collaboration is recurring and similar products or assemblies appear in orders. That’s exactly the type of environment where automation and AI can streamline work and reduce time-to-quote.

Why else does it make sense to use AI in this process?

• The current process is complex and time-consuming
• It requires multiple roles and diverse skill sets
• It leaves room for human error, which can make an order unprofitable — or even lead to rejecting a customer because the correct configuration cannot be assembled
• There is clear room to improve both quality and consistency of outputs

For AI to work successfully, data must be in the right places across the systems that manage it — and those systems must communicate reliably. The foundation is synchronising the ERP system (the source of product information) with a CRM such as Salesforce, where an AI-enabled offer configurator can be built.

[.infobox]The resulting solution is self-service, with AI assistance for configuring offers on the manufacturer's web portal[.infobox]

What does such a configurator look like in practice?

• The customer logs in with their own credentials
• The configurator contains predefined fields with selectable values
• AI suggests the most recent or most frequently ordered components — or recommends suitable alternatives
• AI only allows compatible components to be selected, helping build the most accurate order
• The resulting order is routed to a specialist for review only
• The specialist validates the order and, if needed, confirms details with the customer
• The system automatically generates the offer in the required format and sends it to the customer

This model can evolve from a “classic” configurator into a chatbot or voicebot, depending on how clients prefer to work and communicate. For many customers, moving to a self-service configuration environment will represent a major shift in how they operate.

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Use Case 2: Handling Customer Requests

The second practical example of using AI is a situation where we are the customer of a company that manufactures critical products for our own business or for our own clients. We need to have an overview of the status of our order, possibly change something in it, or find out the expected delivery date.

The current setup often clogs the email inboxes of sales reps as well as general company mailboxes, and it heavily loads the call center and technical specialists. The goal is to create self-service with AI assistance for handling customer requests.

How can such self-service look and work?

1. Login based on the customer’s own identification or order ID.
2. Defining a single source of truth where all order information is stored (usually the CRM).
3. Ensuring that all channels (email, web form, phone, chat) flow into one place (the CRM).
4. Minimizing the need for human intervention.

In this environment, a chatbot — or even a voicebot — connected to the order database and CRM can answer the vast majority of questions. In one manufacturing company where we implemented a similar approach, this led to a significant increase in cost efficiency.

A Solid Data Foundation Is the Key to Success

If you want to use automation and AI in manufacturing in a truly practical way, you need a high-quality data foundation. That means having the right data in an appropriate CRM system — and clearly defining that system as the single source of truth.

Equally important is connecting the CRM to the ERP. Only then does it make sense to scale AI across business processes. A simple rule still applies: if you put AI on top of a mess, it will generate more mess.

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If you want to transform your business, we’ll be happy to walk you through the options so you can achieve long-term growth. Do not hesitate to reach out to us.