An Intro Not Written By GenAI… But I Thought About It!
This past January, a number of professionals descended upon Midtown Manhattan for an industry conference. Amidst the crowded conference floor, technology vendors gathered to showcase their wares at flashy booths, luring in prospective buyers with promises of workflow enhancements (and swag, of course).
As our sales engineering team ran through demos and chatted with prospects, a singular line from a conversation stuck with me. Upon seeing a demo of our new Generative-AI powered offering, a prospect said, “We’ve been talking about AI in products for years. This year, it finally feels real.” And indeed it does! From our own product to SaaS applications we license, Generative-AI integrations are showing up left-and-right. And for every new enhancement to be sold, there are sales engineers who need to understand it inside and out. Here’s what you, a sales engineer, should consider when communicating the value of Gen AI based tools.
Learn the Lingo
Quick quiz: what are inputs and outputs from Generative-AI tools called?
Prompts and completions!
Ok, that might have been an easy one, but knowing the lingo- especially when the rubber meets the road on your own product, is crucial. Just recently, we had a large prospect reach out with a questionnaire that raised key concerns such as:
- How do we plan to test and integrate model improvements?
- How do we work to mitigate bias and discrimination in AI?
- How does your tool deal with hallucinations?
- What guidance do you provide around prompting?
These are just a few of the myriad Gen AI specific questions prospects will ask. This technology can be polarizing, and the job of sales engineers is to instill confidence in its implementation. One of the primary ways of doing this is having strong, consistent answers to questions that demonstrate a strong understanding of the underlying technology.
Action for Sales Engineers:
Consider some team-level training. At Relativity, we leveraged LinkedIn learning, for instance. It’s also worthwhile to set up some sort of internal (or even externally facing) question and answer repository so that sales engineers can have key responses immediately on hand. Especially if you have an RFP automation tool in house, or something similar that is already fit-for-purpose on storing and versioning responses.
Location, Location, Location (of the Data)
Speaking of questions… you’d be hard pressed to find a topic that will come up more often when pitching Gen AI based products than data security. When our organization put together a whitepaper on security and privacy with our Generative-AI approach, our sales engineering team distributed it over 60 times in 8 months. Needless to say, it’s been a popular piece of collateral! A savvy sales engineer should be prepared to speak to their organization’s positions on how their customers’ data will interact with the Generative-AI tools integrated into their platform.
If the integrations fall largely within your existing security policies, then you can potentially leverage existing materials to prevent from having to redo large, AI specific security assessments. These likely contain similar questions as assessments already answered during the sales process. But, at a minimum, sales engineers should understand the value in communicating how and where customer data is processed, particularly as it relates to the existing product boundaries.
Action for Sales Engineers:
Take stock of the content your organization has put out around Gen AI and security, both internal and external. Understand the main talking points and be prepared to speak to them on calls and demos. Just like common functionality questions, a Q&A repository for security related inquiries can be an excellent resource.
“Sigh… everything is AI now. How is this different from your competitors?”
That’s a quote from yet another conference attendee, exasperated and overwhelmed by the sheer number of products claiming to be powered by AI. It’s also a fair question to ask! Part of the key to communicating product value is understanding the differentiation of your particular offering.
What problems do competitor products solve in comparison to yours? Is one a chatbot for end user assistance, and the other designed around using completions as work product? Then there probably is not a ton of competitive overlap. If your competitors’ Gen AI products are solving similar problems, is your organization stronger in areas like security, pace of development, training/support, or strategic partnerships?
A great resource for sales engineers is to leverage customer success stories. If your organization is putting out success stories, sales engineers should be devouring them to weave them into demos and during sales call support. A great way to counteract the type of exasperation exuded by our conference attendee is to drop the hypotheticals, understand their pain, and map your Gen AI solution to it through customer stories!
Action for Sales Engineers:
If you don’t already have them, talk to your organization about creating competitive battlecards. Sales engineers should study these, or alternatively publicly facing competitor info, to understand the market for Gen AI tools in your industry. Explore what early adopter stories you can share, either through your marketing department or anonymized ones from your customer teams.
Putting It All Together
Now that we’ve identified some key considerations for selling Gen AI products, what better forum for a sales engineer to demonstrate all of these concepts than in a demo! Consider a few different options for building out an effective demo:
- Set trap questions that demonstrate expertise. Rather than relying on generic questions like “what do you think?”, use questions that play to your product's strengths. If you are great at mitigating hallucinations, consider asking the audience if they are familiar with the concept of hallucinations, and then demonstrate how your product succeeds. If you know it’s an area where competitive products are weak, all the better!
- Get out in front of common queries. If prospects are constantly asking whether or not customer data is used to improve any underlying models, build that answer into your demo talk track.
- Be specific! As noted above, integrating customer stories in your demo can be crucial to mitigate prospect FUD (fear, uncertainty, doubt) around Generative-AI. New technology will always invite a large amount of skepticism, detailing tangible instances of the product in action can help overcome it.
And Now, A Conclusion Written by Generative-AI
In the fast-paced world of Generative-AI, sales engineers need to master the lingo, address data security concerns, differentiate their products, and showcase their expertise in demos. By learning key AI terms, leveraging existing security materials, understanding competitive advantages, and using real-world examples, sales engineers can confidently navigate client questions and demonstrate their product's unique value. Happy selling!
…
What, did you think this was going to be a whole article on Gen AI that doesn't use Gen AI?!
About the Author:
![Profile photo of Frank Gorman](https://cdn.prod.website-files.com/61c17273335e3e4daf3da6c1/6671aac268fd7db8642c9055_1579811321106.webp)
Frank Gorman is a Senior Manager of Sales Engineering at Relativity. He's spent over a decade as a client advocate and solutions specialist, matching emerging tech to client needs.
An Intro Not Written By GenAI… But I Thought About It!
This past January, a number of professionals descended upon Midtown Manhattan for an industry conference. Amidst the crowded conference floor, technology vendors gathered to showcase their wares at flashy booths, luring in prospective buyers with promises of workflow enhancements (and swag, of course).
As our sales engineering team ran through demos and chatted with prospects, a singular line from a conversation stuck with me. Upon seeing a demo of our new Generative-AI powered offering, a prospect said, “We’ve been talking about AI in products for years. This year, it finally feels real.” And indeed it does! From our own product to SaaS applications we license, Generative-AI integrations are showing up left-and-right. And for every new enhancement to be sold, there are sales engineers who need to understand it inside and out. Here’s what you, a sales engineer, should consider when communicating the value of Gen AI based tools.
Learn the Lingo
Quick quiz: what are inputs and outputs from Generative-AI tools called?
Prompts and completions!
Ok, that might have been an easy one, but knowing the lingo- especially when the rubber meets the road on your own product, is crucial. Just recently, we had a large prospect reach out with a questionnaire that raised key concerns such as:
- How do we plan to test and integrate model improvements?
- How do we work to mitigate bias and discrimination in AI?
- How does your tool deal with hallucinations?
- What guidance do you provide around prompting?
These are just a few of the myriad Gen AI specific questions prospects will ask. This technology can be polarizing, and the job of sales engineers is to instill confidence in its implementation. One of the primary ways of doing this is having strong, consistent answers to questions that demonstrate a strong understanding of the underlying technology.
Action for Sales Engineers:
Consider some team-level training. At Relativity, we leveraged LinkedIn learning, for instance. It’s also worthwhile to set up some sort of internal (or even externally facing) question and answer repository so that sales engineers can have key responses immediately on hand. Especially if you have an RFP automation tool in house, or something similar that is already fit-for-purpose on storing and versioning responses.
Location, Location, Location (of the Data)
Speaking of questions… you’d be hard pressed to find a topic that will come up more often when pitching Gen AI based products than data security. When our organization put together a whitepaper on security and privacy with our Generative-AI approach, our sales engineering team distributed it over 60 times in 8 months. Needless to say, it’s been a popular piece of collateral! A savvy sales engineer should be prepared to speak to their organization’s positions on how their customers’ data will interact with the Generative-AI tools integrated into their platform.
If the integrations fall largely within your existing security policies, then you can potentially leverage existing materials to prevent from having to redo large, AI specific security assessments. These likely contain similar questions as assessments already answered during the sales process. But, at a minimum, sales engineers should understand the value in communicating how and where customer data is processed, particularly as it relates to the existing product boundaries.
Action for Sales Engineers:
Take stock of the content your organization has put out around Gen AI and security, both internal and external. Understand the main talking points and be prepared to speak to them on calls and demos. Just like common functionality questions, a Q&A repository for security related inquiries can be an excellent resource.
“Sigh… everything is AI now. How is this different from your competitors?”
That’s a quote from yet another conference attendee, exasperated and overwhelmed by the sheer number of products claiming to be powered by AI. It’s also a fair question to ask! Part of the key to communicating product value is understanding the differentiation of your particular offering.
What problems do competitor products solve in comparison to yours? Is one a chatbot for end user assistance, and the other designed around using completions as work product? Then there probably is not a ton of competitive overlap. If your competitors’ Gen AI products are solving similar problems, is your organization stronger in areas like security, pace of development, training/support, or strategic partnerships?
A great resource for sales engineers is to leverage customer success stories. If your organization is putting out success stories, sales engineers should be devouring them to weave them into demos and during sales call support. A great way to counteract the type of exasperation exuded by our conference attendee is to drop the hypotheticals, understand their pain, and map your Gen AI solution to it through customer stories!
Action for Sales Engineers:
If you don’t already have them, talk to your organization about creating competitive battlecards. Sales engineers should study these, or alternatively publicly facing competitor info, to understand the market for Gen AI tools in your industry. Explore what early adopter stories you can share, either through your marketing department or anonymized ones from your customer teams.
Putting It All Together
Now that we’ve identified some key considerations for selling Gen AI products, what better forum for a sales engineer to demonstrate all of these concepts than in a demo! Consider a few different options for building out an effective demo:
- Set trap questions that demonstrate expertise. Rather than relying on generic questions like “what do you think?”, use questions that play to your product's strengths. If you are great at mitigating hallucinations, consider asking the audience if they are familiar with the concept of hallucinations, and then demonstrate how your product succeeds. If you know it’s an area where competitive products are weak, all the better!
- Get out in front of common queries. If prospects are constantly asking whether or not customer data is used to improve any underlying models, build that answer into your demo talk track.
- Be specific! As noted above, integrating customer stories in your demo can be crucial to mitigate prospect FUD (fear, uncertainty, doubt) around Generative-AI. New technology will always invite a large amount of skepticism, detailing tangible instances of the product in action can help overcome it.
And Now, A Conclusion Written by Generative-AI
In the fast-paced world of Generative-AI, sales engineers need to master the lingo, address data security concerns, differentiate their products, and showcase their expertise in demos. By learning key AI terms, leveraging existing security materials, understanding competitive advantages, and using real-world examples, sales engineers can confidently navigate client questions and demonstrate their product's unique value. Happy selling!
…
What, did you think this was going to be a whole article on Gen AI that doesn't use Gen AI?!
About the Author:
![Profile photo of Frank Gorman](https://cdn.prod.website-files.com/61c17273335e3e4daf3da6c1/6671aac268fd7db8642c9055_1579811321106.webp)
Frank Gorman is a Senior Manager of Sales Engineering at Relativity. He's spent over a decade as a client advocate and solutions specialist, matching emerging tech to client needs.
An Intro Not Written By GenAI… But I Thought About It!
This past January, a number of professionals descended upon Midtown Manhattan for an industry conference. Amidst the crowded conference floor, technology vendors gathered to showcase their wares at flashy booths, luring in prospective buyers with promises of workflow enhancements (and swag, of course).
As our sales engineering team ran through demos and chatted with prospects, a singular line from a conversation stuck with me. Upon seeing a demo of our new Generative-AI powered offering, a prospect said, “We’ve been talking about AI in products for years. This year, it finally feels real.” And indeed it does! From our own product to SaaS applications we license, Generative-AI integrations are showing up left-and-right. And for every new enhancement to be sold, there are sales engineers who need to understand it inside and out. Here’s what you, a sales engineer, should consider when communicating the value of Gen AI based tools.
Learn the Lingo
Quick quiz: what are inputs and outputs from Generative-AI tools called?
Prompts and completions!
Ok, that might have been an easy one, but knowing the lingo- especially when the rubber meets the road on your own product, is crucial. Just recently, we had a large prospect reach out with a questionnaire that raised key concerns such as:
- How do we plan to test and integrate model improvements?
- How do we work to mitigate bias and discrimination in AI?
- How does your tool deal with hallucinations?
- What guidance do you provide around prompting?
These are just a few of the myriad Gen AI specific questions prospects will ask. This technology can be polarizing, and the job of sales engineers is to instill confidence in its implementation. One of the primary ways of doing this is having strong, consistent answers to questions that demonstrate a strong understanding of the underlying technology.
Action for Sales Engineers:
Consider some team-level training. At Relativity, we leveraged LinkedIn learning, for instance. It’s also worthwhile to set up some sort of internal (or even externally facing) question and answer repository so that sales engineers can have key responses immediately on hand. Especially if you have an RFP automation tool in house, or something similar that is already fit-for-purpose on storing and versioning responses.
Location, Location, Location (of the Data)
Speaking of questions… you’d be hard pressed to find a topic that will come up more often when pitching Gen AI based products than data security. When our organization put together a whitepaper on security and privacy with our Generative-AI approach, our sales engineering team distributed it over 60 times in 8 months. Needless to say, it’s been a popular piece of collateral! A savvy sales engineer should be prepared to speak to their organization’s positions on how their customers’ data will interact with the Generative-AI tools integrated into their platform.
If the integrations fall largely within your existing security policies, then you can potentially leverage existing materials to prevent from having to redo large, AI specific security assessments. These likely contain similar questions as assessments already answered during the sales process. But, at a minimum, sales engineers should understand the value in communicating how and where customer data is processed, particularly as it relates to the existing product boundaries.
Action for Sales Engineers:
Take stock of the content your organization has put out around Gen AI and security, both internal and external. Understand the main talking points and be prepared to speak to them on calls and demos. Just like common functionality questions, a Q&A repository for security related inquiries can be an excellent resource.
“Sigh… everything is AI now. How is this different from your competitors?”
That’s a quote from yet another conference attendee, exasperated and overwhelmed by the sheer number of products claiming to be powered by AI. It’s also a fair question to ask! Part of the key to communicating product value is understanding the differentiation of your particular offering.
What problems do competitor products solve in comparison to yours? Is one a chatbot for end user assistance, and the other designed around using completions as work product? Then there probably is not a ton of competitive overlap. If your competitors’ Gen AI products are solving similar problems, is your organization stronger in areas like security, pace of development, training/support, or strategic partnerships?
A great resource for sales engineers is to leverage customer success stories. If your organization is putting out success stories, sales engineers should be devouring them to weave them into demos and during sales call support. A great way to counteract the type of exasperation exuded by our conference attendee is to drop the hypotheticals, understand their pain, and map your Gen AI solution to it through customer stories!
Action for Sales Engineers:
If you don’t already have them, talk to your organization about creating competitive battlecards. Sales engineers should study these, or alternatively publicly facing competitor info, to understand the market for Gen AI tools in your industry. Explore what early adopter stories you can share, either through your marketing department or anonymized ones from your customer teams.
Putting It All Together
Now that we’ve identified some key considerations for selling Gen AI products, what better forum for a sales engineer to demonstrate all of these concepts than in a demo! Consider a few different options for building out an effective demo:
- Set trap questions that demonstrate expertise. Rather than relying on generic questions like “what do you think?”, use questions that play to your product's strengths. If you are great at mitigating hallucinations, consider asking the audience if they are familiar with the concept of hallucinations, and then demonstrate how your product succeeds. If you know it’s an area where competitive products are weak, all the better!
- Get out in front of common queries. If prospects are constantly asking whether or not customer data is used to improve any underlying models, build that answer into your demo talk track.
- Be specific! As noted above, integrating customer stories in your demo can be crucial to mitigate prospect FUD (fear, uncertainty, doubt) around Generative-AI. New technology will always invite a large amount of skepticism, detailing tangible instances of the product in action can help overcome it.
And Now, A Conclusion Written by Generative-AI
In the fast-paced world of Generative-AI, sales engineers need to master the lingo, address data security concerns, differentiate their products, and showcase their expertise in demos. By learning key AI terms, leveraging existing security materials, understanding competitive advantages, and using real-world examples, sales engineers can confidently navigate client questions and demonstrate their product's unique value. Happy selling!
…
What, did you think this was going to be a whole article on Gen AI that doesn't use Gen AI?!
About the Author:
![Profile photo of Frank Gorman](https://cdn.prod.website-files.com/61c17273335e3e4daf3da6c1/6671aac268fd7db8642c9055_1579811321106.webp)
Frank Gorman is a Senior Manager of Sales Engineering at Relativity. He's spent over a decade as a client advocate and solutions specialist, matching emerging tech to client needs.