AI-guided selling enables analytics to move from descriptive to predictive and prescriptive analytics. The process uses customer and sales data for a scientific, data-driven approach to understand buyer processes and behaviors.

How Manufacturers are Leveraging New Technology to Meet Customer Demands
How Manufacturers are Leveraging New Technology to Meet Customer Demands

Adrian Penka & Duncan Steels | Capgemini

Tell us about yourself and your role with Capgemini.

[Adrian] I have been with Capgemini for 23 years focused on supply chain and operations transformation across a number of industries, including auto, aerospace and defense, and discrete and process-based manufacturing. While having focused in several areas within supply chain consulting, my specialty is in procurement and supply chain strategy – business models, operating models, and process improvement. 

[Duncan] I’m a brand and experience practice leader for Capgemini in North America. I drive cross-sector experience strategy, design and operating model transformations for marketing, sales, commerce and service organizations. 

 

How do you see the customer experience evolving as new capabilities are introduced to manufacturers?

This is an exciting time for manufacturers. Organizations embarking on a digital transformation project have the opportunity to put customers and consumers at the heart of the business operations. And as many of us know, a robust and engaging customer experience is a key differentiator in the market today.

While recent changes in the current climate will likely require less in-person meetings and more digital or contactless engagements, this allows for new, innovative channels to help evolve the customer experience. Voice search, AR and AI all encourage customers to seamlessly move between (and within) channels to maintain a consistent experience.

Interestingly, websites and portals will become less important as these new experiences accelerate customers more quickly and directly to the information and services they are looking for at the “point of need” in their own journey. Also, when built properly, digital twins will allow customers to find products or collections of products based on what they want or need their technology to do (in customer or end-customer terms) and not on manufacturer-defined product criteria. Manufacturers that can collect and hold large amounts of data and translate it into actionable insight will develop a competitive advantage.

 

Give us a brief overview of AI-guided selling.

AI-guided selling enables analytics to move from descriptive to predictive and prescriptive analytics. The process uses customer and sales data for a scientific, data-driven approach to understand buyer processes and behaviors (rather than a more prescribed sales process). This creates a more objective view of the customer pipeline stage. It also enables optimizations in the sales process based on historic and propensity modelling to help identify which customers are more likely to buy and which customers might drop out of their buying process, and alerts for interventions and recommended actions that are mostly likely to be effective. AI functionality can also optimize sales call planning and adjust the engagement accordingly.

In addition, manufacturers can advance their AI sales capability by not just looking at what they sell (and at what price) to which customer and across which channel … but who will purchase a product or service, which channel will be most responsive, and what message will resonate best. 

 

What can manufacturers gain from creating a more holistic view of customers (e.g. customer intimacy, personalization, AI-guided selling, for example)?

It’s important to distinguish that increasingly there are two types of customers that must be considered: 

  • End customers: From this perspective, a more holistic view of end customers for manufacturers can offer important consumer-driven insights for product and service improvements and understanding new product development/R&D needs. By giving a voice to customers, it can also help deliver better experiences by understanding sentiment and perception towards their products/services.

  • Direct business customers: Manufacturers can identify cross-selling and up-selling opportunities based on direct customer buying patterns once they have a more holistic view of their customers. With segmentation, that includes a better understanding of behaviors, attitudes and needs. Lookalike modelling will help find more prospects to target. Improved insights into how direct customers interact with the manufacturer (i.e. where and when) will help grow engagement opportunities based on customer preferences. 

 

Do you see manufacturing's existing experience in safety emphasis being helpful in today's environment, or is this situation too unique for them to pull from past learnings?

Yes, I do think we have some existing toolsets used in pre-pandemic times that could prove useful in reinforcing a set of expanded safety practices. Some examples include well-documented policies and procedures along with clear and consistent work practices. But as we’ve explored here, many new capabilities need to be developed before they can be fully integrated. 

 

What advice would you give to a manufacturer in today’s environment who is trying to adapt to all these changes we are experiencing?

An important piece of advice is to make sure manufacturers are properly leveraging technology to glean relevant data and insights. Typical paper processes do not have access to this kind of valuable information, so it’s crucial to trust new capabilities to deliver on this.

 


 

About Adrian Penka
Adrian leads Capgemini’s Operations Transformation Group in North America and the Global Procurement Transformation practice. He has over twenty-two years of experience specializing in Supply Chain strategy, Procurement strategy and transformation, with a strong background across the supply chain discipline. Adrian has also helped a number of companies with Growth Strategy, Business Model, and Operating Model initiatives.

Duncan Steels
Duncan is a brand and experience practice leader for Capgemini in North America. He drives cross-sector experience strategy, design and operating model transformations for marketing, sales, commerce and service organizations. Duncan’s consulting and transformation expertise has been developed in companies ranging from top 10 healthcare and financial services companies to successful technology companies.

 
The content & opinions in this article are the author’s and do not necessarily represent the views of ManufacturingTomorrow

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