Generative AI and retrieval-augmented generation (RAG) have become essential tools for chemical technical sales teams.
Chemical Manufacturing
April 18, 2024
Have you considered the new possibilities generative AI brings to chemical manufacturing? Even if this is the first time the idea has hit your radar, it’s worth taking a closer look.
Generative AI has come a long way in the last few years. Today, it’s transforming the way that sales teams in chemical manufacturing connect, share, and help drive revenue and business growth.
Think of it like this: If your technical sales team is like a finely tuned sports car, GenAI is like upgrading the turbocharger, increasing performance through access to information.
If that analogy doesn’t do it for you, perhaps diving into some of the most common use cases will hit a little closer to home. Let’s take a look.
Generative AI in chemical manufacturing transforms productivity with the click of a button, like the foot on an accelerator. Sales reps can provide a quick query and have the answers or product information they need within seconds, helping leaders improve every level of their sales team.
Training will inevitably look slightly different from one sales team to the next, but information is a thread of commonality.
Chemical manufacturing sales require in-depth product knowledge, an understanding of the manufacturing processes, and external pressures impacting the buying process like environmental, social, and governance (ESG).
Ramping up new team members can take months with traditional training, costing valuable time and money. The traditional process often involves spending time in the field with seasoned reps, where information is absorbed one conversation at a time.
GenAI takes this process from 0 to 60 in weeks instead of months. By giving new reps access to a never-ending bank of information that can be dialed up at any given time, the entire sales rep onboarding process is streamlined. Questions can be answered in real time, making it easier for new technical sales reps to build their pipeline and start contributing to the overall revenue goals of the organization.
But improved product knowledge isn’t limited to new reps. Seasoned team members also benefit from GenAI — an increasingly urgent need given chemical manufacturing’s constantly evolving sales landscape, growing product portfolios, and increased competition.
Chances are, you can pinpoint the members of your team who hold the most expert knowledge. Even in enterprise operations, it may be that only a select few are considered subject matter experts (SMEs) or technical product experts. This is because knowledge and information have been traditionally siloed across technical sales, technical services, and R&D organizations.
The idea of “phoning an expert” is less than ideal. It delays the sales process. Customers buying specialty chemicals expect every technical sales rep they encounter to have a deep level of knowledge and expertise in the industry.
GenAI can simplify the process by which knowledge is passed from one rep to another, preparing every sales rep to answer questions thrown their way. Tools like GenAI-powered subject matter avatars are great at breaking down the walls within the organization.
Resources that were once out of reach (or hidden) are instantly available, making it easier to share information and keep everyone on the same page and performing at a high level.
Do you want to speed up the sales cycle? There is no speed limit on the information highway, and with GenAI as your co-pilot, your reps can put the pedal to the metal.
All jokes aside, there is a direct correlation between improved knowledge and sales success. Tapping into generative AI tools at any point in the sales cycle addresses concerns, highlights key features of the product or product portfolio, and provides specific applications and use cases.
In addition to providing internal information, these tools can perform competitive benchmarking of your products and others in the marketplace. Reps can then take a more proactive approach to address pricing concerns, key differentiators, and other curveballs when going head-to-head with a competitor on an account.
At the end of the day, all of these components facilitate richer, more meaningful conversations that lead to better deals for both the buyer and seller.
As customer demands increase, improving your technical sales and services strategy is essential. Great technical sales teams drive revenue. The very best sales teams entrench a customer, building relationships that make it easier to ward off potential competitors.
In this particular area, GenAI is incredibly powerful. By tapping into organizational knowledge, technical sales reps can see emerging trends, provide recommendations when supply chain disruptions occur, and quickly troubleshoot product questions or application issues.
Through its data-driven approach, GenAI provides chemical manufacturing sales reps with deeper insights they can transform into results, enhancing overall efficiency and customer satisfaction.
Driving sales results in the chemical manufacturing industry used to rely on a small handful of product knowledge experts. Today, generative AI turns every member of your team into an SME, opening the door to better conversations, deeper trust, and more consistent sales results.
At Nesh, we provide your team with GenAI tools that drive sales in your complex industry. Our subject matter avatars are designed to enhance knowledge across the entire organization — from new team members to seasoned professionals. Talk with the Nesh team to see how GenAI can help your company starting today.
Want to learn more about potential GenAI use cases for Chemical and Materials companies? Check out The Future of Chemical Sales: 6 GenAI Use Cases.
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Generative AI and retrieval-augmented generation (RAG) have become essential tools for chemical technical sales teams.
Unlock the power of generative AI with Nesh to elevate every technical sales rep in your specialty chemical company.
In their basic format, search engines operate on Information Retrieval (IR) principles and are commonly used for search.
