Guide: How to Sell AI Technology
Table of Contents
In the B2B software space, Artificial Intelligence is one of the hottest trends of post-COVID. So it should be easy to market and sell AI, right? Selling and marketing AI software are incredibly difficult. A major reason is that the media and many companies give the impression that AI technology is magic. AI is not magic, AI solves real problems.
The general public thinks (wrongly) that they know what AI is and what it does. More worryingly, they are afraid of technology. A 2017 survey found that 70% of people are actively afraid of robots and AI technology, worrying about their jobs and even their safety. People believe that Artificial Intelligence is some sort of maleficent conscious technology that is coming for their jobs and to rule the world.
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Outlandish Promises as a Sales Method
This puts Artificial Intelligence companies who try to market and sell AI technologies in a difficult space. On the one hand, there is a bidding war on outlandish promises where company A states “AI will take all of our jobs in 5 years” to which company B answers “Actually, AI will rule the world in 10 years” and so forth and so on. These promises deliver two things: short-lived PR and “tourist” prospects with no project, no budget, and a lot of time to waste. The second option is to stand against the existing narrative, sell a realistic product, and risk looking like old technology, leading real prospects with budgets to call “respectable” companies such as Microsoft, IBM, or Accenture.
My business partner and I spent the better part of the last decade trying to find answers to these exact questions. Through trial and error, we finally hit upon the way forward. This guide will give you a brief overview of what we learned. We hope it will help you not to make some of the mistakes we made when we first started.
To cap it all off, startups who market and sell AI often raise Venture Capital. VCs expect scalable growth fast, meaning that startups have very little time to test and learn and create a sustainable marketing and sales AI process. So how do you market and sell AI B2B software?
Failing to Sell Artificial Intelligence Licenses Kills Startups
Many B2B AI companies have incredibly long sales cycles, some lasting well over a year. In general, these companies have a sales cycle that follows the “out of the box” CRM stages: Interest Raised, Qualification, Decision Maker Identified, Proposition, Negotiation, Close Won/Lost. They sell an amazing technology able to deliver performances never reached before. And then they become a consultancy and die out. Here’s how they fail to market and sell AI:
1 – Pitching Artificial Intelligence
These AI companies find that their first client meeting is spent explaining what AI is and isn’t and then pitching or presenting their unique AI software. Discovery calls are spent on performance and features.
If a prospect responds to this type of marketing, then a follow-up meeting is organized for technical analysis. The prospect naturally brings in their IT team, who are often against implementing any new technology. After this, a proposal is priced and sent. Generally, the IT pushes for a POC to test your technology and the business line tells you that POCs should be free.
2 – The Valueless POC
So you build a POC, which takes a few months, and then present it to an even larger group of people. IT critiques your methods and how they might implement them into their systems and the front line users express concerns that the AI might take their jobs. But everyone agrees that technology is “cool”. You then present your proposal for a production application. But all of the conversations are about your technology, implementation, and the cost of the technology.
3 – The Endless Pilot
Often the POC was led by IT to “test the technology”, meaning the use case chosen is worthless. The business, therefore, wants to go through a pilot phase to deploy the AI and see if there is a positive ROI. The pilot requires more work on your side and while it is paid, you generally don’t make any recurring revenue with it. The pilot could take a few months or even 6 months in some cases.
4 – Time to Close the Deal
Then finally you try to close the deal. Again presenting the cost of your solution. But this price is the same one you presented earlier in the sales cycle and doesn’t take into account all the time (and money) you’ve spent trying to land this customer over the last year. Since you have not focused on business problems, your price is compared against the results of the pilot. Sometimes customers will tell you that the software was very powerful but they don’t think that they tried the right use case, this pushed you back to the POC stage with a whole new use case. Other times, they will say that they loved the pilot, but don’t have any budget to go any further.
When you sell technology, a curious and technology-focused prospect will want to try the technology. If the technology is tried, that’s a success for them. You just never got to where you wanted.
I’ve heard startups complain when enterprise accounts lead them on a wild goose chase for months and they fail. But truthfully, it’s the startups’ fault. By selling technology, you attracted prospects who never cared about solving business problems.
Know Your Customer (and her context)
When asked about how he marketed the Ford Model T, Henry Ford supposedly said
“If I had asked [people] what they wanted, they would have said they wanted a faster horse”.
Now, this quote has been widely debunked and Henry Ford is certainly not the best role model. However, there is a truism here. To quote another questionable role model, former US Secretary of Defence Donald Rumsfeld,
“there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns[i]”.
For startups who market and sell AI, disruptive technology is solving problems that people have but don’t even know there is a solution. In short, AI solutions to problems rest firmly in the “unknown unknown” category with people looking for contemporary solutions not new AI-based ones.
Example: How to Sell AI in Medical Diagnosis
Basically, many AI softwares are so disruptive that they fix problems, which exist, but which people don’t even realise there is a solution to. Let’s look at a quick example:
Early detection is key to increasing cancer survival rates. The problem is that error rates are very high, with professionals generating false positives 30% of the time. Everyone agreed that this was a problem but the general answer to the problem was more training for medical professionals or hiring more medical professionals, so they were not overworked and therefore prone to mistakes.
Artificial Intelligence technologies like Lunit, Aidence, and others are identifying tumors more accurately and faster than doctors. The technology will red flag areas that need further examination. These technologies could fundamentally change the way we treat cancer. However, the underlying technology has been around for years, so why were they not adopted sooner?
The medical community was not looking for technical solutions and had been burnt by AI promises in the past. AI companies in this space were seen as “cool”, “futuristic” and not trustworthy (because they were AI).
A few innovators in the medical space gave the technology a go and were willing to share their success stories. In an industry where best practices are shared easily, testimonials were the key marketing strategy leveraged to open new accounts.
Build your Pipe to Sell AI SaaS with Content and A/B Testing
Many software companies which market and sell AI are truly disruptive innovators for example companies like Mind Foundry, an Oxford-based AI company that brings to market automated machine learning (AML). It is truly disruptive, but it doesn’t fit into an existing market or solve a problem that people are looking for, with the possible exception of people who have already deployed complex machine learning projects and know-how time-consuming and expensive they are. However, disruptive technologies like this are some of the most high-growth potential and the most exciting to be a part of. But this still leaves the question for marketers: how do I generate demand? It’s easy to generate large numbers of useless leads in the AI space, the key is to generate the right leads for your business.
Define the ideal customer to sell AI to?
The first step is to figure out who your ideal customer is. This may seem obvious but when you dig deeper this can be a really difficult step for a company. How can you generate demand if you don’t know where the demand should come from. You need to be very specific. For example, you don’t want to say “we target the banking sector”, you want to say:
“We target CFOs in London working in International banks with both UK and US branches who are overwhelmed by complex regulatory requirements and looking for how new technologies might help them turn their regulatory burden into a competitive advantage.”
You need to be as targeted as possible and then you need to test your hypothesis, remember to think about what makes an ideal customer for you and what makes an ideal vendor for them. Then make sure there is a match.
What are their problems?
Once you know who you are targeting, you need to understand their pain points. This is a fairly researched-based step. You need to write down the problems you think your customers have and ask them which of these problems are the most painful. The objective of the problem step is not to find your customer’s headaches, but to find the problem that forces them to break the status quo. The problem is the base on which your startup will market and sell AI, not the technology.
Don’t be afraid to be wrong
You’ve built your company with your blood sweat and tears but sometimes that doesn’t allow you to be objective. If you can’t talk to customers, speak with analysts or consultants outside your company, you need to get perspective and objective feedback. Identifying the problem that customers are willing to pay to solve can help you to target the exact people you need to reach out to both for outbound and inbound marketing.
Google is your Friend and content is your best friend
Now that you know what problem you solve and who you solve it for, it’s time to get to work. What do we do when we are looking to solve a problem? We ask Google.
Ask yourself: when a prospect begins searching for a solution to a problem you solve, what is the first thing she types in Google? The answer is your first hypothesis. Publish SEO-optimized content around these specific keywords and track how many meetings you are getting with the content and if your content is allowing you to meet the right executives.
Don’t just Sell AI! Become the market leader in your niche
As you build your content, fine-tune the messaging and get your first customers, you will find a market to grow in. Once you find it, own it. When you market and sell AI, be ambitious! To generate real demand you need more than just content marketing, you need to raise visibility through analyst briefings, a robust account-based marketing approach, and a website that is laser-targeted around the problems you solve and who you solve them for. It’s tough being number 1, so make it easier by focusing on a niche.
Focused Demand Generation allows you to get in front of great leads. Great leads are decision-makers looking to solve specific problems. Very often, they have tried to solve their problem with in-house solutions but are not satisfied.
A well-thought-out, intentional, and target demand generation approach will position your company as a thought leader and help you market and sell AI. Your website will be optimized for keywords (like “market and sell AI” in this article!) around the exact problems you solve and you will begin to build a powerful inbound marketing machine. Thought leaders pick their customers and can raise prices with almost no impact on their customer base. Sound great, doesn’t it?
Don't Generate Buzz, Sell AI that solves Real Problems Honestly
A study undertaken by VC MMC Ventures found that a full 40% of AI Startups have no elements of AI in their software at all. But it is not just start-ups who feel the need to embellish the truth, even IBM Watson has been called out for, shall we say, exaggeration. Why is there the temptation to say you have AI technology when you don’t or to exaggerate what your technology can do?
Discussing with executives how to market and sell AI technology, I came across the term the “AI Effect”. I wish I’d known about it earlier, but this theory describes why companies feel the need to exaggerate. The AI Effect argues that once a user understands how technology works, they no longer consider the technology to be AI. Or, to put it another way, the AI Effect defines AI magic and any other “non-magic” technology as “not real AI”.
The AI Effect encourages companies to obfuscate. But let’s be honest, AI technologies are not exaggerating in a bubble. We live in a world of fake news and what some have worryingly called a “post-factual era”. However, I am an optimist and I believe that companies that market and sell AI dishonestly will ultimately be punished for that behavior. More importantly, the exaggeration has been taken to such an extreme that it is hurting the bottom lines of even the biggest players with prospective buyers afraid that all AI is just smoke and mirrors.
Why Being Honest is a Good Demand Generation Strategy
A change is coming and the companies who are honest and helpful to their customers will be the main beneficiary. In the book The Tipping Point, Malcolm Gladwell argues that to effect a major change, or market and sell AI in our context, you need mavens, connectors, and salesmen. He calls this the “Laws of the Few”.
“The success of any kind of social epidemic is heavily dependent on the involvement of people with a particular and rare set of social gifts.”
Three Key Ingredients of Major Change
Mavens are the influencers, who share ideas and impact opinion. These are the influencers you will target as part of your marketing campaigns.
Connectors are expert influencers. Leverage Honesty as a marketing tool and they will reward you.
If you look at Gartner or Forrester research around AI and speak with analysts, they’re approach is that AI isn’t magic. They focus on solutions not technologies and in analyst briefings they push vendors who market and sell AI very hard on any areas where they suspect exaggeration. Moreover, if you look at Gartner’s 2019 Hype Cycle for AI you will see that almost no AI technology (except speech recognition) has reached the plateau of productivity. Instead, the majority are right around the peak of inflated expectations. If you know Gartner hype cycles, you know that the Trough of Disillusionment follows the peak of inflated expectations. Vendors who market and sell AI need to be aware of this when drafting content or prepare collateral.
Salesmen. To continue our analogy, this means you, the AI companies. You need to sell your vision for AI and your honest analysis of how it does (and doesn’t work).
Customers have heard enough AI lies
AI exaggeration is at a tipping point. Buyers are sick of being lied to by companies who market and sell AI and as businesses struggle they will no longer have extra money at their disposal to try out technology.
This creates an opportunity for the honest AI players. By articulating a positive vision for AI and actively debunking AI myths, you will position yourself as “the adult in the AI conversation” and you will be seen as an honest broker.
Getting your first website visitors, meetings and full events may be tougher if you market and sell AI without making wild claims, but hold the line and you will succeed.
Focus on Customer Pains not Technology to Sell AI
We can agree that selling magic isn’t a successful growth strategy. But I would take it a step further: You need to stop trying to market and sell AI technology altogether. People don’t buy technology, they buy solutions.
Look at your smartphone. Did you buy it because it has a faster processor, machine learning, or more RAM? Or, did you buy it you want to take great pictures of your kids, keep in touch with your family and friends and stream Netflix on the Underground?
Technology is a tool. We buy technology to solve problems, cut costs, make more money or make our lives easier. The best way to market and sell AI is to forget the AI and focus on what you solve.
Does your technology make lives easier, cut costs or boost revenue?
To create a powerful sales process, it is critical to understand what your product brings to market. You should have identified what specific problem your product solves in the Demand Generation step. By classifying this problem in a category, you will be able to create a sales process and pricing that works.
More often than not, AI allows businesses to generate a combination of three value propositions:
Sell AI which Makes Life Easier
This is more of an overarching idea or a soft “value added”. Solutions that generate convenience focus on removing a headache for customers. Solutions that help customers become more agile, manage workload peaks or get rid of time consuming tasks often fit this category.
For example, I worked with a software company that automated the writing of management reports. One of the major selling points internally on Wall Street is that by automating the writing of the reports with a click, analysts could make it to their kids football matches on the weekend. This was certainly not the number one value added of the software but it was one of the most compelling.
Help customer cut costs
Many vendors market and sell AI which automates business processes and therefore market themselves as cost cutting solutions. This is a trap.
Focusing your software on cost cutting can make it easier to market and sell AI, but you risk what we call the “WalMart effect”. If people are focused only on saving money, they will expect your software to be cheap as well. They will be focused on “bargains” and will easily replace you with another vendor who markets and sell AI which is similar but cheaper, as soon as it becomes available.
This is not to say that Cutting Costs is a bad value added. Instead, always combine the cost cutting value proposition with more qualitative aspects, such as enhanced quality or agility.
Sell AI which Boosts Revenue
Solutions that boost revenue, such as sales tools and marketing intelligence are very powerful and quite easy to market and sell AI. Which business isn’t looking for more customers?
However, if you sell AI which allows customers to sell more, then make sure you can prove it. You need to have a detailed explanation backed up by numbers and testimonials.
Also, your sales team should drive customers to only use the product if they track the results, so that they can see the impact for themselves and deploy the product across the company.
Disruption or helping customer Sell More, Cut Costs and gain Convenience
AI technology can fundamentally change business models by generating value in all three categories. In fact, the largest AI projects that I have managed do just this.
AI-Powered drug discovery is a great example of this. Pharma companies can use AI to pour over their existing drug trail information and even their failed drug trials. Using millions of data points, the technology can very quickly identify potential new uses for existing or failed drugs. This kind of data mining is not possible to do manually and so it creates a whole R&D stream while simultaneously cutting the cost of creating new drugs since these existing or failed drugs have already cleared many of the (expensive) hurdles needed to bring a drug to market.
If your AI Tech is truly disruptive, you are creating a startup that is both interesting and risky. Indeed, when a new technology does everything, it is very easy to get lost in the woods.
Our recommendation for vendors who market and sell AI which can generate many different value proposition categories is simple: Pick one and focus.
The Amazon Example
Amazon is a tremendous success stories of the past two decades. It demonstrated that with eCommerce, consumers could have access to more choices at better cost. The rating system reduces the risk of being deceived and reviews give better product transparency. Prime demonstrates the immense value generated by customer loyalty and gives some of that value back with free shipping and films. AI is incredibly powerful with features such as “Inspired by your Purchasing History”. But before Amazon did all that, it started with a simple value proposition as a first step towards a grand vision: “Amazon.com, the world’s biggest bookstore”.
If you believe your company can be as disruptive as Amazon, start selling books and take the first step.
Build a Sales Process from Day 1 to sell AI at scale
The first foundation on which startups who market and sell AI are built is Demand generation. Once content is published and your marketing team is getting your sales team in front of the right executives, the sales team takes over and works to close the deal.
The major issue we find with many startups is the lack of a sales process. Without sales process, the company bases its success on “hero sales”, or the ability of founders to sell a product by showing their passion. Hero sales is a trap, as when customer buy the product, they are actually buying the founder. It’s essential for the first handful of customers who buy a MVP. But basing a company on charisma sees sales plateau very quickly. Startups can’t market and sell AI on weak foundations.
We recommend to professionalize the sales process as quickly as possible, with experiments and a clear track. This allows the company to onboard additional sales over time without having to learn how to sell when the train is already at full speed.
Qualify your Leads – 50% of Success in Sales happens before the first call
A sales conversation is just as much for you to see if the prospect is a good fit, as it is for them to see if they want to keep talking to you. Good technology salespeople ask more questions than they answer. This qualification step should be a first call and we generally build checklists for our customers to make sure the sales person or inside sales stays on message.
Too often salespeople see getting the prospect to agree to a second meeting to be a “win” and some companies even reward them for what they are filling their pipe with. This problem is particularly common in companies with long sales cycles. If you have to wait 6-8 months to sign a contract you need some “small wins” to keep motivated. But the truth is, you really want to fail fast with prospects. Sometimes the sales cycles are too long because the qualification step is not well done or is focused too much on technology.
Sales Intelligence You Need. to collect ASAP
- Solution Fit: What problem do they have and can our software address it?
- Market Fit: Does the lead fit our agreed target market?
- Goals: How does this project fit into the leads overarching business goals (is it critical or not)?
- Authority: Am I talking to the right person?
- Budget: Have they budgeted for this?
- Timeline: When are they expecting to be in production
Solution Fit: What problem do they have and can our software address it?
Before contacting you, what pages did your prospect read? Which whitepapers did she download? By tracking how your prospect reached you, you will be able to understand the problem they are looking to solve. Successful firms who Market and Sell AI know the problem their customers have better than customers themselves.
Market Fit: Does the lead fit our agreed target market?
You need to make sure you are selling in the market that you’ve agreed to target. If your sales team is selling in other markets, your pricing may be wrong and you may not be able to deliver (and sell) as fast as you want.
Use LinkedIn to gather information and be ready to refuse taking a meeting.
Goals: How does this project fit into the leads overarching business goals (is it critical or not)?
Many companies have websites, PR announcements and hired new employees. By seeing where the company is heading, you can often understand whether your solution will be strategic or a side project.
Focus your energy only on companies for whom you will be strategic.
Authority: Am I talking to the right person?
This is an obvious step in any sales process but can be forgotten. You need to make sure you are talking to the right person in the organisation.
If you are not speaking with the right person, take the call politely and ask to speak to the right person. They may know each other.
“Bob, I’m happy we spoke today about how our startup can help you solve your problem. However, whenever we have had a successful project deployed with customers, the Head of Marketing’s opinion was always critical. Do you believe you could help me organize a call with the Head of Marketing?”
Budget: Have they budgeted for this?
Before the call, you can already answer this question partially by looking at the number of employees they have, find market intelligence on what technology they currently use and how they price their products to understand if they are low cost or high end. When building your process to market and sell AI, make sure your buyer persona includes information to prove that the buyer has a budget.
I once worked with a company selling BI solutions. To gather intelligence, we would look at their recruitment page for technology positions available. The company looked for technical staff who had knowledge of the technologies they were using. If the technology was open source only, we would skip. If the company used expensive technologies, they would be our target.
Timeline: When are they expecting to be in production?
Timeline is often one of the first questions a sales manager asks during the first call. Before the first call, always look on social media for announcements, as you will sometimes understand the timeline better than the person you have on the phone. This information gathering ahead of the call is critical to market and sell AI, as AI deployments often require momentum and creating consensus.
For example, when a company raises Seed round, they have 18 to 24 months to reach $2M ARR for Series A. If you sell a Lead generation tool and the person on the phone says that the project needs to start in the next 6 to 12 months, you can disagree, explain why they need to sign in 6 weeks if they want to reach their objectives and send a purchase order.
I’ve done it: the conversation may be slightly conflictual as many executives are not used to being questioned, but in the end I signed the deal and the customer never had time to call competition.
The first meeting is always the Discovery Meeting
The objective of qualifying leads ahead of the first call is to focus 100% of your energy on prospects which will want to close.
When done right, the objective of the first call is not just to collect information. Surely, you will validate with customers what you deduced from your research. But, the true objective is to sit down, listen to your customer and prove that you understand them. Differentiate from every other tech company and build your brand as the adult in the room.
Many tech companies see the first meeting as an opportunity to show a demo, but it isn’t. If your prospect wants a demo, you can send them a Youtube video that they watch afterwards. When you organise this first call, make sure expectations are clear:
You want to understand their problem to make sure that you can help them and that there is a fit for working together.
How do you act as the expert and demonstrate a fit? By drilling down into your customer’s problems until you hit hard numbers. Ask “Why” as many times as you can before it becomes awkwards and collect hard numbers (growth targets, customer churn, etc). The numbers should be the pain that is driving the company’s goals.
List of topics to cover during first meeting
- What are your prospects goals? You need KPIs here that you can use later one.
- Find the cost of inaction? What is their pain and what does it mean to do nothing?
- Have they tried solutions before? Do they solve the solution manually? Did they try building a solution in-house?
- Which datasets are they using? Can they send you a sample of the data?
- What is the ideal solution to their problem? Ask them to dream so you get a sense of what they really would like to have.
By asking these questions and drilling down on each point, you should be able to map out the customer problem clearly. Leverage this understanding when preparing a proposal for a roadmap from status quo to final success.
Remember, 90% of AI tech companies talk about features to market and sell AI. The company who wins does not have the best technology. The company who wins demonstrates that they understand their customer best.
Great Proposals that Sell AI Start from the Promise Land
If you followed your process, you know what your customer’s pain points are. You know their goals and what the cost of inaction are.
Once you have all this information you have the opportunity to adopt a value-based pricing approach but that is a topic for another ebook. For the purposes of this document, we will assume that your pricing work is done and well suited to your market.
Like all bad marketing, many proposals focus on the what. For three vCores of processing and 1TB of data, customer pays $X. Focusing on what is the best way of getting stuck in budget negotiations and pricing issues.
Leverage the Promised Land to avoid sinking in POCs
- Your customer has a problem, solving the problem means deploying your solution across the organisation. The promised land is based on assumptions, both technical and business. You need to prove that the data is available and the impact is clear.
- To prove these assumptions, you may need to go through a pilot phase were a limited number of uses deploy the solution. Propose the pilot with a recommended number of users, who they should be, why and what KPIs to track. If the KPI milestones are reached in a certain amount of time, contract goes to full deployment automatically.
- Before deploying the pilot, a POC may need to be created for technical assumptions. How tough is it to connect our tools together and collect the data? Define the POC, milestones and state that if the POC succeed, pilot starts automatically.
When drafting a proposal, never propose a tool or a feature. Propose a roadmap from status quo to Promised Land. This will allow you to build momentum, not have to negotiate every step of the way, and once more filter out customers from tourists.
If the customer only wants to talk POC, she’s not a customer
If a customer agrees with the roadmap and milestone but wants to only sign a small deal for a POC first, “just to see”, ask why. Does she not believe in your value proposition? Are the objectives wrong? Startups who market and sell AI and the underlying vision well are able to sell the end of the process, not just the first step.
Whatever happens, do not budge. You cannot accept to sign a POC or pilot if there is no production licence at the end of the tunnel. And don’t be afraid to fail fast.
Dos and Don’ts to Sell AI
Some of these are obvious but we’ve seen experienced sales people make these mistakes. Obviously, this isn’t a comprehensive list but it’s a good place to start.
Don’t Be Afraid to Say No
This is critical. If you adopt the sales process, it is designed to help you to fail fast. This means that if at the end of the first call, you think it’s not a good fit for you, then you need to say no. Maybe build relationships with others in your space so you can say “I am sorry we can’t help you here for the following reasons… but we know company XYZ does this work and could be a big help”. This approach keeps prospects happy so if they have a future project, you are the first on this list. But no matter how you do it, you need to say NO to projects that are outside your targeted market, or who need solutions that are not quite what you offer. Market and sell AI by remaining focused.
If it’s not in the CRM, it didn’t happen
If you want to build a scalable sales and marketing machine, you need to adopt a CRM that fits your needs. CRMs alone don’t increase sales but they can help you to scale your efforts and for you to diagnosis problems in your sales process. However, you can only diagnosis problems if the data is appropriately put in your CRM. By this, we don’t mean lots of emails with the customer and lots of notes. Instead, you need to update the CRM at the key stages of the sales process and you need to have your CRM modified so you can capture as much structured data about the process as possible. That structured data is critical for reporting and for automation.
Practice what you preach and Automate
You need to practice what you preach. AI companies sell automation and the best way for you to scale your sales and marketing is to automate as much as possible. You can automate:
- The back and forth to set meetings
- Prospecting emails
- The generation of Proposals
- Collection of Customer Data via chatbots and forms online
Automation helps you to do more with less and keeps your sales team focused on what they do best, selling your product.
This eBook has given you a brief overview of what we learned in over a decade of experience spent working on techniques to market and sell AI technology.
Successfully scaling an AI company requires rock-solid positioning, strong pricing, a strategic marketing approach and a fully aligned sales and marketing team. It has been our experience that having outside help on these strategic initiatives is critical. It not only gives an outside perspective but also brings different ideas and strategies to your team.
Interested in learning more about how our services can help your sales & marketing? Contact Us