AI for product marketing (7 actionable use cases)

Using AI for merchandise promotion can assistance you execute crucial tasks faster than you can manually. And by connecting your existing tools and environment up automations, you can addition your output during keeping a individual in the iteration to inspect the results.

In this guide, I’ll stroll you through seven use cases for AI in merchandise marketing, throughout three tiers:

1. Using chatbots for merchandise marketing
2. Connecting your existing merchandise promotion tools to AI
3. Building agents to execute tasks automatically

How to use AI efficiently for merchandise marketing

To use AI for merchandise marketing, create a project inside your favorite AI tool (e.g., ChatGPT or Claude) to keep all tasks connected alongside merchandise promotion in one place. This yields tailored results according to your business, your product, and your messaging.

I’ll display how to create a project in Claude. Click “Projects” in the left-hand sidebar. Then click the “New project” button. 

Give your project a name and description, and afterward click “Create project.” 

Once inner your project, you can add instructions if you desire to define rules for Claude to follow. For example, you can define a tongue it should use or any words and phrases it should evade in outputs. These instructions are helpful but optional.

Next, add environment records by clicking the “+” icon in the “Context” window, afterward click “Add content content.” 

Give your content satisfied a title, afterward paste in the particulars in the “Content” division and click “Add Content.”

For the workflows I'm going to display you, I propose adding three environment files:

1. A business brief: Includes data concerning your business, merchandise details, ICP, and competitors
2. Approved messaging/positioning: Includes brand positioning statements, industry, chief and secondary audiences, value propositions, and differentiators
3. Sales call transcripts: Includes genuine client tongue and particular use cases as environment the AI tool can diagram on at any time

You may additionally desire to add merchandise spec sheets, existing battlecards or conversation tracks, and any another data that volition assistance the AI to improved comprehend the merchandise that you’re looking to launch/market.

For the purpose of this article, I'm going to use a fictional example of a feedback tool called Signalwell. Here's the business concise I added as a environment file:

Your project won't automatically update as you initiate new products and tweak features and positioning. So, treat this akin a living document that you edit and update as your merchandise or endeavor evolves. 

Now that you’ve created your project and added your environment files, you can commencement really using AI for particular merchandise promotion use cases. 

Tier 1: How to use AI chatbots for merchandise marketing

AI chatbots are finest for merchandise promotion tasks that you don't desire to run automatically. 

This makes Tier 1 awesome for one-off checks and crucial tasks that you lone have to execute occasionally. For example, whenever your positioning shifts or a competitor launches a new product. 

Use case #1: Messaging consistency checker

Use AI to justify you’re efficiently communicating your product's value and how it solves your mark audience's problems.

For example, you can use AI to difference the copy you scheme to use on a new landing leaf alongside your existing approved messaging document. The AI can analyze the new copy for any inconsistencies or edits you power desire to create before publishing. 

I motionless propose manually checking the output to justify it’s exact and doesn’t merge hallucinations. But if you have a lot of copy to check, having AI verify the messaging can emblem the most crucial issues a lot faster.

Use the following immediate to inspect your content’s messaging (make certain you add your approved messaging to the project or the prompt):

Act as a merchandise promotion satisfied reviewer. Check the leaf below against our approved messaging and positioning (see project files).

Identify any areas anywhere the satisfied contradicts, weakens, or drifts from the approved messaging. Flag unsupported claims, inconsistent terminology, and places anywhere the intended spectators or value proposition is unclear.

For all issue, display the applicable copy, explain the problem, and propose a concise fix. Don’t emblem harmless wording differences if the underlying communication is motionless consistent.

Page or copy to review: [paste satisfied or URL]

You could use this immediate for revenue decks, assistance center articles, onboarding email sequences, partner and reseller copy, and equal job listings to justify you’re using accordant messaging. 

Here’s an example output for our fictional business, Signalwell. You can see the AI tool compared the copy to the project's approved messaging file. It suggested idiosyncratic issues, stated the problem, and offered a fix that I could verify and implement.

How to obtain this further

Here are a few ways you could get additional out of this messaging consistency checker:

• Run the checker throughout existing pages whenever your positioning shifts to quickly place anywhere your copy no longer matches your new positioning
• Run the immediate alongside distinct AI models, as one example power place an inconsistency that another one didn’t deem value flagging 
• Paste in a competitor's leaf alongside your messaging doc, and ask the tool to acknowledge claims anywhere you could stance your own merchandise as the stronger option

Use case #2: Generating client discussion questions

Use AI to put together client discussion questions whenever you’re trying to study item particular concerning your customers’ behavior. 

For example, create client questions using AI if you’re looking to:

• Refine your positioning
• Understand why customers toggle to or from your product
• Validate new merchandise use cases
• Improve your onboarding process

Use this immediate to build client discussion questions:

Act as a merchandise promotion investigator assisting me prepared client interviews.

Product: [One- or two-sentence description]

Customers I am interviewing: [role / section / business category / applicable characteristics]

What I am trying to do/learn: [e.g., refine positioning, comprehend why customers switch, validate a new use case, enhance onboarding]

What we currently believe: [any hypotheses or assumptions you desire to test]

Create a [30-minute] discussion guide according to these requirements:

- Start alongside two to three warm-up questions that established the customer's function and context

- Prioritize questions concerning genuine former behavior complete hypothetical behavior

- Don’t compose foremost questions or citation our preferred answer in the question

- Cover the customer's problem, how they earlier solved it, alternatives considered, purchasing criteria, triggers, objections, and desired outcomes anywhere relevant

- For all crucial question, provision one to two optional follow-up probes

Below is an example output from Claude. You can see that it organized the questions into groups and provided follow-ups depending on the customer's reply to the chief question. 

Claude additionally flagged conflict points from another environment records that I had uploaded to the project and afterward formulated multiple questions about those conflict points. I didn’t immediate Claude to do this. 

This is an example of the benefits of uploading endeavor environment and former revenue calls whenever you're trying to use AI for merchandise marketing. Since Claude had this environment in the project, Claude is capable to diagram upon the environment at any period it thinks it’s helpful for the output.

How to obtain this further

Here are a few ways to get additional out of this discussion inquiry generator:

• Upload revenue call transcripts to the AI tool and ask it to acknowledge recurring objections and points of friction, so reps can location them first in forthcoming calls
• Run this immediate multiple times alongside distinct models or equal distinct AI tools to get a wider assortment of questions
• Paste in call transcripts from conversations that used these questions, and ask the tool to acknowledge ways to refine them additional to get additional helpful answers from customers

Use case #3: Building competitor battlecards

Use AI to build competitor battlecards that assistance your revenue teams quickly difference your merchandise against a particular competitor during calls. 

Battlecards can quickly rotate into redundant or outdated as competitors alter their pricing, initiate new features, or change their own messaging. And an AI tool can quickly collect the latest data and put it all together into a formatted battlecard.

Use the immediate below to build your own competitor battlecards:

Act as a rivalrous intellect expert construction a one-page revenue battlecard.

My product: [One to two sentences]

Competitor: [Name and URL]

Our ICP: [Who you market to]

Evidence: [Two to five revenue call transcripts, closed-lost notes, or assistance tickets anywhere this competitor came up]

Steps:

1. Search the web for this competitor's current positioning, pricing, and center features. Give me a origin nexus and a date for all actual claim.

2. Read my evidence. Pull the exact words prospects used concerning this competitor. Quote them directly.

3. Build a one-page battlecard alongside these sections:

 - How they stance themselves (their words) vs. how buyers depict them (my evidence)

 - Why we win: Three reasons, all tied to a origin or a quote

 - Where we lose: Two genuine gaps

 - Objection handling: The genuine exception tongue from my evidence, alongside a response

 - Talk track: Three sentences a rep can use in a call, using the prospect's phrasing

 - Their apt assault on us: What you'd compose on their battlecard concerning us

Mark any pricing or characteristic assertion you couldn't verify against a live origin as unverified. Give me two versions: a formatted one-page card, and plain content I can paste into our revenue enablement tool.

Here’s an example of a battlecard that this immediate produced. Note that the immediate additionally generates a plain content type that you can copy and paste anyplace you need it to go. 

How to obtain this further

Here are a few ways you could get additional out of an AI-generated competitor battlecard:

• Upload a manner guide or ocular examples, so your AI tool can format your battlecards exactly as you desire them to look
• Use the immediate to create a battlecard for your competitor against you to assistance place gaps in your messaging
• Run this immediate regularly to justify your battlecards remain up to date

Tier 2: How to nexus AI to merchandise promotion tools

Tier 2 involves connecting AI to merchandise promotion tools to unlock additional complex capabilities.

Connecting tools via connectors and example environment protocols (MCPs) allows your AI tool to additional effortlessly collect data, possibly from multiple places. 

Use case #4: Running an SEO competitor analysis 

Use AI to run an SEO competitor analysis by connecting your AI tool to Semrush via the MCP. This lets you analyze your market much faster than you would be capable to do manually. 

By looking at hunt petition for conditions connected to your product, you can see the tongue your buyers use at measure and which competitor messages and pages run integrated traffic.

Use this immediate to run a competitor inspection using the Semrush MCP:

Use Semrush data to analyze petition about this market:

My domain: [domain]

Competitors: [domains]

Market: [country/region]

Product/category: [short description]

Identify the competitor product, feature, and use-case pages attracting meaningful integrated demand.

Group the chief hunt themes into problems, use cases, features, category terms, and difference terms. For all theme, display applicable keywords, hunt volume, intent, and which competitors rank.

For the highest-traffic competitor leaf in all theme, open the leaf and record: the center commitment in one sentence, the evidence they use (customers, numbers, and integrations), and who the leaf is written for.

Highlight areas anywhere multiple competitors are targeting the identical theme, petition appears meaningful, competitors have powerful pages, or our location has small equal coverage.

Then rotate the findings into merchandise promotion recommendations, including messaging to test, pages or use cases value developing, client investigation questions, and rivalrous claims value investigating.

Here’s an example output for this prompt. Note that I used a genuine domain for this (frill.co), since our fictional endeavor doesn’t have a domain that I could use. 

You can see the AI tool sorted its results into themes. And it included hunt volume, intent, and keyword difficulty.

Below the array of keywords, the tool highlights the pages driving the most integrated traffic and data concerning what those pages contain. 

Finally, the AI phase explained why this data matters. In this case, it suggested that nearly no competitors are appearing in the hunt results for crucial ache points, and this may portray an chance for us to mark that alongside a product-first page. 

Further downward in the output, the AI tool provided apparent recommendations of messaging to test and equal pages or use cases value developing. 

This is an example of anywhere hunt data can be helpful for additional than fair SEO. It can additionally provision merchandise marketers alongside possible messaging and use case ideas. 

How to obtain this further

Here are a few ways you could get additional out of operating an SEO competitor inspection alongside AI connected to another tools:

• Ask the AI tool to aspect paid keywords into its inspection to comprehend which messaging pillars competitors are prioritizing alongside their paid spend
• Run this inspection regularly to comprehend hunt petition trends and how that maps to your own launches or repositioning efforts
• Use the Semrush MCP to analyze new markets that you haven't launched in yet to comprehend hunt petition and possible messaging angles

Use case #5: Connecting to a cognition base

Connect your AI tool to your cognition basis (Notion, Google Drive, etc.), so it can drag insights from your existing documentation. 

A lot of merchandise promotion activity involves synthesizing evidence that's scattered throughout discussion notes, closed-lost records, merchandise requirements documents (PRDs), and call summaries. Connecting your cognition basis method the AI says all of it whenever you need it to, without you having to discover and paste everything in manually.

For example, you can ask AI to drag the most average objections from your former client interviews and inspect them against your messaging doc. That can inform you which objections your revenue squad currently has no approved answer for.

Add connectors in Claude by clicking “Customize” in the left-hand sidebar. Then hunt for the connectors you need.

In ChatGPT, click “Plugins” in the left-hand sidebar, afterward hunt for the ones you need.

For our fictional endeavor Signalwell, we have a Notion dashboard that contains data concerning the company, alongside alongside messaging documentation, PRDs, competitor notes, and more. 

I prompted Claude to hunt the client interviews repository and discover ache points that were mentioned in additional than two interviews. I could afterward use this data in another tasks (for example, updating messaging docs). Or I could continue this on to revenue teams as a catalog of the chief ache points we resolve that they have to be highlighting.

Next, I prompted the AI tool to peruse the PRD leaf concerning our fictional business’s upcoming Gong integration, alongside alongside our messaging and positioning doc. I afterward asked it to compose a one-page FAQ to bring revenue reps up to speed alongside the planned features. 

How to obtain this further

Here are a few ways you could get additional out of connecting your cognition basis to AI:

• Check the connector directories in ChatGPT and Claude for the tools your squad already plant in regular (e.g., your CRM, call recorder, or analytics platform), afterward appearance for new ways to drag that data into your prompts
• Combine multiple connectors in one prompt. For example, you could peruse your positioning document in Notion and drag rivalrous petition data from Semrush to discover anywhere your claims overlap alongside messages your competitors already get traffic for.
• Combine tool connections alongside the another use cases in this guide. For example, you could run the messaging consistency inspect without adding updated positioning records to the AI tool directly, and alternatively fair keep it updated in your cognition base.

Tier 3: How to build an AI merchandise promotion agent

Tier 3 is merchandise promotion automation: construction repeatable processes that an AI tool runs for your squad on a schedule.

I used ChatGPT for the two use cases below since you can agenda tasks without any complex setup. If you're using Claude, you can do this alongside scheduled tasks on a paid plan. Click "Scheduled" in the left-hand sidebar. You can additionally agenda recurring activity in Claude Code. 

Use case #6: Analyzing Reddit threads for key term mentions

Build an AI agent that automatically scans Reddit for applicable threads that citation you, your products, or your competitors to communicate your product promotion strategy.

Your mark spectators is apt using Reddit to ask questions and discover recommendations, making it a precious origin of data concerning your prospective customers and the tongue they use. For example, the r/CRM subreddit has 15K weekly visitors, and users regularly ask questions about which CRM to use. 

However, manually checking Reddit all day for mentions of your products or your competitors takes period and effort. Building your own merchandise promotion AI delegate streamlines this task. 

Use this immediate to set up a regular subreddit scraper delegate that looks for applicable threads formerly per day:

Check [r/subreddit1, r/subreddit2, r/subreddit3] for posts and comments from the former 24 hours mentioning [competitor names, our merchandise name, category terms].

For all match, report:

- Thread heading and link

- What was said, in one or two sentences

- Sentiment: positive, negative, or neutral

- Type: purchasing intent (asking for recommendations or alternatives), complaint, assistance question, or broad chatter

- Whether it supports or contradicts any assertion in our messaging doc (see project files)

Rules:

- Add new thread IDs to the log (create this log on the archetypal run). Skip item already in this log in forthcoming runs. 

- Rank buying-intent threads first.

- If nothing matches, answer "No mentions in the final 24 hours" and stop. Don't extend for free connections.

Turn this into a scheduled project that runs [e.g., daily] at [time].

Here’s an example output from ChatGPT according to the immediate above. I used one of Signalwell's competitors, Canny, as the chief term to target, and I asked ChatGPT to execute the inspect daily. No Canny mentions came up that day, but the delegate surfaced threads concerning Pendo and Productboard.

How to obtain this further

Here are a few ways you could get additional out of a Reddit-scraping agent:

• Connect the tool to your workspace or Slack channels to get a regular study automatically
• Create a akin project for another places your buyers display up, akin another industry forums or assessment sites
• Use the data you collect to refine your messaging docs and client interviews that you generated in Tier 1

Use case #7: Tracking competitor updates

Build a competitor update tracking delegate to automatically inspect your competitors’ websites for changes to features, pricing, and messaging.

Your competitors are apt changing their pricing, shipping new features, and rewriting copy on their website constantly. Tracking these changes manually is cumbersome, but it leads to helpful insights you can use to modify your own merchandise promotion strategy. 

Use the immediate below to set up your own competitor update tracker that checks key competitor pages automatically:

Every Monday at noon, run the following checks and study changes (if there are no changes, additionally log this):

1. Check the following URLs for [competitor] for changes published during the final seven days:

• [Pricing page]
• [Official publish notes]
• [Changelog]
• [Product blog]
• [Help center documentation]

Compare them alongside what you observed previously. 

For the pricing page, study cost changes, packaging changes, renamed tiers, added/removed limits, and changes to liberated trials or liberated plans.

For another pages, study changes that could power positioning, rivalrous differentiation, exception handling, merchandise parity, mark customer, or packaging. Ignore insignificant bug fixes.

2. Check the homepage and following chief merchandise pages for [competitor]:

• [Homepage]
• [Product leaf 1]
• [Product leaf 2]
• [Product leaf 3]

Identify matter changes to headlines, category language, mark audience, center value proposition, important evidence points, and featured use cases. Don’t study cosmetic copy edits unless they alter the apparent positioning.

Include the origin URL and exact evidence in all cases.

I ran this immediate for one of Signalwell's competitors, Canny. Note that I gave the delegate a made-up "previous" snapshot of Canny's location to difference against, so the changes in these screenshots are not genuine Canny changes. I did this lone to display what the agent's output looks like.

The delegate flagged a higher Pro cost and a smaller liberated allowance compared alongside that snapshot, alongside alongside changes to another features on the pricing page. It additionally compared the copy on Canny's use case pages to place changes in headings and shifts in general messaging.

How to obtain this further

Here are a few ways you could get additional out of a rivalrous update tracker:

• Feed the outputs rear into your battlecard prompts to justify they’re up to date
• Use this delegate to analyze competitor job listing pages to place signals concerning new markets they may be entering 
• Set up multiple agents to run these checks for multiple competitors automatically 

Create your own AI merchandise promotion agent

There are nearly endless ways to use AI for merchandise marketing, but the use cases complete are ideal starting points for your own AI merchandise promotion workflows. And there are many tools you can nexus to create your AI workflows equal additional powerful.

One specified tool is the Semrush MCP. Connect to it today to provision your AI tools precious keyword and hunt achievement data to enhance your workflows.