What Is an AI-Powered Go-to-Market Strategy?

Increasingly powerful AI models are quickly changing how businesses create, market, and sell their products. Instead of resorting to educated guesswork, new AI models can help companies use real-time data to plan and execute their go-to-market strategy. 

This solves a challenge many businesses face – finding the best way to enter a market and driving demand for their solution. 

Armed with the right insights, you can reach the right people at exactly the right time.

So whether you’re an experienced marketer or new to running a business, here’s a closer look at how you can use AI to grow faster and power your GTM strategy.

What is an AI-powered GTM strategy?

Bringing a new product to market (or expanding an existing one) is tough. 

GTM strategies help you plan out how you’ll introduce your solution to your target market, and a good GTM plan answers questions like:

• What problem does your product solve?
• How does your product solve it?
• Who are your customers?
• How will you reach them and convince them to buy your product?

Successful GTM plans aren’t one-dimensional. They cover several key components such as:

• Understanding your audience: Target market, ideal customer profiles, buyer personas
• Positioning your product: Unique value proposition, product positioning
• Selling & distribution: Pricing models, sales channels, sales strategy
• Marketing & engagement: Messaging, customer buyer journey, marketing strategy
• Measuring progress: Success metrics, KPIs
• Enabling your plan: Budget, resource allocation

An AI-powered GTM strategy uses AI tools to engage your target audience quicker and more efficiently. Regardless of whether you prefer a simple or detailed GTM approach, AI can handle some of the heavy lifting like:

• Real-time lead identification
• Outreach and follow-up automation
• Message personalization 
• GTM playbook execution

What are the benefits of using AI in a GTM strategy?

Using AI for your GTM strategy allows you to work faster with less, as well as make data-driven decisions.

Here are some other advantages of powering your GTM plan with AI.

Research and analysis

AI tools can process large swaths of data in minutes. GTM strategy planners can leverage that power to discover product-market fit and better position their offer.

For example, a startup launching a new project management tool for small and medium-sized enterprises (SMEs) can use an AI-powered market intelligence platform to analyze thousands of forum discussions, social media posts, and reviews of competitors’ products to find out which features existing solutions lack.

This AI-powered research may reveal that many users are unhappy with the level of task automation in existing products. The startup can then adjust its GTM strategy to emphasize advanced task automation as the main product benefit, positioning its product as exactly what users need.

Targeting

GTM strategy planners can use AI tools to refine their ICP and target their communication more precisely.

Imagine a company launches a new data management tool that uses AI to analyze historical data from B2B leads. Further analysis reveals that IT managers at mid-sized healthcare firms are twice as likely to request a demo of their product as IT teams at other kinds of firms. 

Thanks to this AI-powered insight, the company knows that it can quickly target this lead segment and start gaining traction toward product adoption.

Personalization

Personalized messaging at scale is a huge use case for AI. You can send messages that contain deep, meaningful personalization, saving you from relying on templates with basic personalization.

Here are some areas where AI can personalize messaging for your GTM strategy:

• Recipient’s role – AI can quickly adjust the content and messaging based on a role. It might share what’s under the hood for CTOs while highlighting ROI for CFOs.
• Recipient’s industry – AI can review and reference relevant news, trends, and concerns related to the recipient’s industry.
• Experience with a competitor – If a recipient had a bad experience with a competitor, AI can highlight features in your product that might solve the problem where the rival product failed.
• Interaction history – AI can tailor follow-up messages based on the latest action taken by the lead, such as text message or a DM on LinkedIn. 
• Website visitors – AI can adjust messages to visitors who checked out your pricing page, your demo page, or a combination of both, making it easier for you to retarget visits.

Doing all this manually would take a lot of time and effort. But with AI, you can outline personalization rules and have the AI execute them for net-new leads on autopilot.

Efficiency and productivity

With AI, teams can automate time-consuming GTM tasks and focus on more value-adding activities.

AI can take over the lion’s share of lead research and nurturing, email personalization, and CRM data management. 

That’s where building a team of humans supported by AI can yield huge benefits. 

Imagine a small SaaS company gets flooded with inbound requests during their product launch. Instead of manually going through them one by one, the team can use AI to automate lead qualification and nurturing. 

When presenting a go-to-market plan to potential investors, it’s worth explaining that your company will maximize efficiency by using AI tools to handle a large volume of tasks with a small team. That’ll answer a question often asked by decision-makers (“How will you do this?”) and show that you’re keeping up with technology advancements.

Data-driven decision-making

GTM strategies deal with a high degree of uncertainty, but that doesn’t mean they should rely on guesswork. AI can analyze data and provide insights in real time for more accurate decision-making.

For example, Company A wants to test its lead list before launching its product. It might run A/B tests to figure out which type of outreach will get results.

Here’s the challenge.

A good A/B test needs several weeks. But startups run at an extremely fast pace, which puts time at a premium. 

You can use AI tools to optimize A/B testing and potentially forecast results from several days instead of weeks. This allows you to iterate your outreach based on test results, and potentially max your performance during the product launch.

6 steps for implementing AI in a GTM strategy

Before you implement AI in your go-to-market strategy, you’ll need a plan.

Here are 6 steps you can take to build AI into your GTM plan.

Define your objectives

The first step is to define the goals of your GTM plan. 

Think about what a successful product launch will look like and how long it should take. Then break this ambitious goal down into smaller, more manageable objectives.

Here are a few examples:

• Main goal – Onboard 100 high lifetime value (LTV) early adopters by the end of month three.
• Positioning goal – Outline your value props for your ideal customers and likely buyers.
• Outreach goal – Reach out to 500 potential early adopters in month one.
• Conversion goal – Convert 20% of leads engaged into paying customers by month three.

There’s no rule of thumb on how many or what kind of goals you should have in a GTM strategy. 

But as a starting point, you should set objectives that are SMART (specific, measurable, achievable, relevant, and time-bound).

Check data quality and quantity

An AI tool that can power a GTM strategy is only as good as the data it’s trained on. That’s why the next step is to determine what data you can use to train your AI assistant. 

You’ll want to look into:

• Competitor data (market intelligence, customer reviews of rival products)
• Website analytics data
• Lead database
• CRM data (from early sign-ups or your existing products)
• User behavior data

If you’re a startup launching your first product, you might not have much CRM or user behavior data. In this case, you’ll need to collect market data about how users interact with products similar to yours.

Check your data for gaps or inconsistencies (e.g. missing contact data or misspelled names). An advanced AI tool might be able to fix some of these, and your team will have to handle the rest.

Decide which AI tool will meet your needs

The AI tool you go with has to be capable of executing your GTM.

Think about tools in terms of the jobs they’ll do:

• Lead qualification – Scores and prioritizes leads with the highest intent
• Competitive insights – Tracks user discussions about competitor products on social media
• Outreach – Personalizes email sequences according to the recipient’s role, industry, experience with rival products, and recent interactions
• Intent research – Monitors channels like LinkedIn posts to see who’s leaving likes and comments

Based on the jobs you want AI to do for you, look for an AI tool that can cover most or all of them.

And don’t overlook the value of a solution that gives you insight into buyer intent. Running campaigns that target stronger buyer signals will lead to more conversions.

Assemble a team

Although some AI tools run on autopilot, they still need the right people to train and oversee them.

A GTM AI team will commonly have:

• GTM engineer
• Growth marketer or marketing specialist
• Account executive or sales specialist
• Data scientist or data analyst
• Domain expert

Each role has its own responsibilities.

The growth marketer irons out the messaging and any copywriting. The account executive closes deals in the pipeline and steps in whenever the sales AI needs an assist.

The data scientist analyzes the data and translates the data insights into actionable tactics. The domain expert adds clarity to behaviors and practices.

And the one tying all this together and making sure the AI’s running correctly? The GTM engineer.

Start small and iterate

Rather than launch AI across your entire GTM strategy, it’s better to test it first on small parts. 

Here are some examples of where to start:

• Use AI-driven personalization on a batch of 100 prospects
• Put 30% of inbound requests through AI scoring and see if AI scores as accurately as your human team members
• Run an A/B test with basic and AI-created versions of a cold email

Review the results of these small tests against target KPIs. 

If AI doesn’t seem to deliver notable results, tweak it (by changing settings or the default prompt) until you meet your goal. After that, you can scale the AI tool to handle all of your GTM outreach.

Monitor and optimize

For best results, you should constantly monitor AI performance and adjust as needed. 

Here are some metrics to evaluate performance:

• Email open rate
• Response rate
• Conversion rate
• Number of demo requests
• Number of sing-ups
• Average deal size
• Monthly recurring revenue (MRR)

AI can self-improve when implemented with a feedback loop. For example, if you give the AI tool information about which outreach emails perform best, it will increasingly use its winning go-to-market tactics in future emails.

By following these six steps, even a small team can set up an AI tool to make the GTM strategy successful.

Best practices and tips

Here are some practical tips for successfully building AI into your GTM strategy.

Align AI with your company’s goals

GTM objectives come first and AI is just a tool to achieve them. 

Think of what GTM goals can benefit most from AI. Can it help you generate more leads, drive conversions, or close sales deals faster?

Start implementing AI in the GTM areas with the highest priority. 

If that’s lead generation, set a specific goal regarding the type of leads you want to target. For example, you may want to prioritize those easiest to convert, high-LTV leads, or vocal brand advocates. After that, you can set your AI tool up to focus specifically on those prospects.

Encourage a data-driven culture

AI thrives on quality data, which means you’ll have to collect and feed data to the AI on a daily basis.

Make sure that all GTM team members understand the value of data for training AI. They must document all their market research and interactions with leads in a form that’s easy for AI to process (e.g. Excel spreadsheets) so that it can produce insights they can use to refine their GTM tactics. 

For example, if AI points out a specific lead segment as most likely to convert, it makes sense for your team to focus on this segment – and feed back into the AI the results of approaching them.

Promote cross-functional collaboration

To execute a GTM strategy, your marketing, sales, and product teams must work together. Make sure everyone is on the same page regarding the use of AI and can feed data into it and access its output.

Use teamwork tools like Slack, Confluence, or Jira for teams to coordinate their effort as they prepare a product launch. Create a shared AI dashboard so everyone can keep track of the data they need to provide to the AI tool and use AI insights to refine their approach to leads.

Provide training and support

Not all team members will know how to work with AI. Make sure that everyone who needs AI training receives it.

Many AI vendors provide free guides and educational videos about using their tool for the best results. Reviewing these will be a good start for your GTM team. If the vendor has customer support, the team shouldn’t hesitate to use it if they run into technical issues that FAQs and other resources don’t cover.

Fine-tune AI continuously with feedback

AI tools learn from data. They’re an evolving asset rather than a static tool, which is why GTM teams need to feed the AI data on which GTM tactics worked and which didn’t.

You can automate feedback loops by integrating the AI tool with your CRM platform. For example, you can integrate AiSDR with HubSpot for the platform to receive updates in real time about email performance, new leads, and closed deals.

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Common mistakes to avoid

Unless you’re teaming up with an experienced GTM engineering team, getting the most out of your AI tool will take a bit of trial and error. However, you can avoid common pitfalls from the very start.

Over-reliance on AI

AI is powerful, but it can’t replace human strategic vision and creativity. It can’t be expected to understand what kind of product you want to launch, what audience you want to attract, or what impression you want to make on your leads.

You need qualified team members to validate AI outputs, especially when you’re just beginning to train it. 

For example, an AI tool prompted to optimize open rates for cold emails might crank out shallow, clickbait-y content that doesn’t convert into demos. A competent team member can spot that and revise the prompt for better results.

Neglecting data quality

Incomplete, outdated, or missing data might steer AI-powered GTM tactics in the wrong direction. 

For instance, if you feed AI data from an outdated CRM database, it might identify leads who are no longer relevant or high-priority, and the GTM team will waste time chasing them. 

To avoid this, make sure that any data you feed to the AI tool is accurate, complete, and current.

Lack of clear objectives

When assigning tasks to AI, you need to know exactly what you want it to achieve and set very specific goals. While AI can identify high-intent visitors or drive demo sign-ups, you’ll need to create prompts that tell it how, or it will stick to whatever default scenario it was wired for and end up causing your GTM campaigns to focus on things you don’t need.

For example, an unprompted AI might prioritize website views, while you need more conversions. But if you write a prompt telling AI to focus on conversions, it will act accordingly.

Ignoring change management

As advanced as any AI tool may be, team members can’t use it effectively if they don’t understand or trust it. People will have to spend extra time and effort to master AI, so they need to understand why it’s worth it. Explain to your team the value that adopting AI will bring to the sales process. 

Make it clear that training an AI tool to support your GTM strategy takes a certain amount of time and data. Even if the preliminary results aren’t ideal, don’t let your team dismiss AI as unfit. Impress upon them that they need to keep fine-tuning it until it shines.

Automating your entire GTM strategy at once

It takes a good deal of experimenting to achieve a perfect fit between your chosen AI tool and your GTM strategy. That’s why it’s best to roll AI out in phases and watch the results. If they’re short of excellent, then you might need to make a few tweaks.

Don’t automate your entire go-to-market strategy until the AI begins to outperform the human team consistently on all tasks you intend to use it for.

3 AI tools for your GTM strategy

The right AI tools can save you considerable time and money while improving your GTM strategy’s results.

Here are three AI tools you can put to good use for your GTM strategy.

AiSDR

AiSDR is an AI-powered sales assistant that comes with all the features outreach teams need. 

Here are a few of the features AiSDR brings to your GTM strategy:

• Sales personas – AiSDR offers the most flexible, detailed sales personas on the market to help you drive demand among your ideal customers. You can teach it to write emails like you, or you can use one of the email frameworks available in the framework library.
• Intent research – AiSDR searches companies and leads for signs of strong buyer intent, such as recent funding rounds, news mentions, tech stacks, and hiring intent.
• GTM plays – AiSDR automates high-impact GTM plays like outreach to website visitors, product champions, lookalike audiences, new hires, and LinkedIn social signals.
• Multichannel sales outreach – AiSDR engages leads through email, texting, and LinkedIn, and creates call scripts and syncs them to your HubSpot CRM.

AiSDR is ideal for teams who rely on emails and LinkedIn messages to drive demand and sales.

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Copy.ai

Copy.ai is a specialized GTM AI platform with a strong focus on sales and creating marketing copy. 

Three standout features include:

• Content creation – Copy.ai delivers various types of copy, including SEO articles, thought leadership articles, case studies, social media posts, and more.
• Translation and localization – You can have a copy instantly translated into multiple languages at a native speaker level.
• Inbound lead processing – You can configure Copy.ai to automatically engage inbound leads.

Copy.ai is good for teams that struggle with writing good sales copy like paragraphs, social media captions, and product descriptions. You can also use it to create blog outlines.

Spiky.ai

Spiky.ai is a sales AI platform with a focus on identifying winning outreach tactics and quickly scaling them across the team.

Here are some of Spiky.ai’s strengths:

• Fine-grained real-time feedback – Spiky.ai provides extremely detailed feedback on each sales team member’s conversations with prospects, scoring their talking speed, talking time, and tone of voice
• Pipeline visibility – It tracks metrics across the sales pipeline in real time and displays them in easy-to-understand graphs.
• Personalized coaching – This AI tool can act as a sales coach for each team member, evaluating various aspects of their performance, such as call momentum and playbook size, and tracking progress over time.

Spiky.ai can benefit GTM teams that want to scale the winning tactics of a stellar team member.