By Alex Niemi in Product — 22 Mar 2025

How Product Marketing Drives Inside Sales Success for Early-Stage SaaS Products (Part 2)

No product marketing website? No product. It’s that simple.

And, if your product marketing website isn’t EXCELLENT or if you’re not consistently creating and distributing compelling long-form content, then your chance of gaining any meaningful traction is minimal.

And, if you don't have robust analytics and event tracking across every digital touchpoint of your product ecosystem, you're incapable of making informed strategic decisions and are essentially steering your business blindfolded through a competitive minefield.

In Part 1, I made the point that timing is an overlooked obstacle to Inside Sales because your leads rarely need your product when you contact them—they don't have "intent" (to use a buzzword).

In this article, I’m going to talk about the solution to the timing issue, which is to have:

A focused product marketing website that has sufficient content and depth for visitors to educate themselves on its value proposition.
A great product with a self-serve model (e.g., free trial/tier) that allows potential clients to independently engage with your product and prove to themselves that it has value.
Robust product analytics to understand the user journey, establish funnels, evaluate conversion rates, coordinate cross-functionally with a shared understanding of the relevant data and metrics, all with the goal of optimizing communication and outreach to your users.

Going back to the Dave’s Daycare example: Even if I happen to have a need for daycare services when I receive Dave’s voicemail, if I can’t find Dave’s Daycare online and vet his business myself, I’m not interested. There’s no way that I’m dropping my kids off at Dave’s place without being able to verify that he’s legit.

It’s the same with products.

People don’t make “buy” decisions based on a single source of information. It doesn’t matter how good your pitch deck is, or how many times you go over it with them, or how many logos you have in your deck; they won’t buy it unless they can verify that it’s worth their time and money.

Here’s how a typical person (we’ll call her Kate) ends up trialing and buying a SaaS product (we’ll call it ProductAI) from start to finish.

Kate’s reading something online, and it happens to mention or have a link to ProductAI. She might’ve been browsing Reddit, LinkedIn, Substack, Quora, Medium, StackOverflow, etc. Or, she’s already using software (e.g., Segment) that cites ProductAI as being an integration. But, ProductAI is irrelevant to what she's currently working on, so she doesn't waste any time looking it up.
Because Kate is a busy professional with a million things to do, she doesn't think about ProductAI again until...
A year later, it pops up in something that she’s reading online. This time she checks it out; i.e., she clicks a link in whatever she’s reading or she Googles “ProductAI.” If the link that she clicks takes her to an incongruous website that isn’t reflective of the product, she bounces. End of story. Or, if nothing comes up when Kate Googles it, there’s nothing left to do. End of story. But, let’s assume that ProductAI does have a website and that Kate visits it.
She scrolls around a bit, and if there's an explainer video, she’ll watch it. If the website is compelling, focused, targeted, and conveys value TO HER and FOR HER CURRENT OR PERCEIVED FUTURE NEEDS, then she might bookmark it… but maybe not.
If the Product Marketing site really resonates with Kate, there’s a chance that she’ll put ProductAI into a different [mental] category of “stuff that I want to try out as soon as I have some free time.” This is the best possible outcome at this stage, but it’s usually not the case. However, this is where all products should strive to get with their Product Marketing website. Continuing on…
A year later, Kate is searching for a new job on LinkedIn and comes across a position at ProductAI. The job isn’t quite right for her — she’s looking for Engineering work, and this job is in Marketing — but she follows the company on LinkedIn just in case a more appropriate job opens up.
A week later, ProductAI posts something interesting on their LinkedIn page, and it shows up in Kate’s newsfeed. It’s a link to ProductAI’s blog and an article about a new ML classifier model that they just released. She checks it out, thinks it’s valuable enough that others would be interested, and so she shares it with her internal team on Slack. Thus, 12 other people at Kate’s company are introduced to ProductAI.
At this point, ProductAI has seen Kate enough times to start retargeting her. So, she starts to see more ads in the margins of the pages she visits when she’s researching stuff online. She ignores all of them because Kate, like all engineers, is smart, doesn't like being tracked, and doesn’t want to reward unscrupulous behavior. Nonetheless, she still likes ProductAI but doesn’t yet have a need for it.
Two months later, ProductAI posts a link on LinkedIn to another blog article that they’ve just written about the newest version of their classifier model. This time, the article is immensely interesting, technical, deep, thoughtfully written, and very detailed. It prompts Kate to sign up for ProductAI’s newsletter.
Every week from that point forward, Kate receives an email from ProductAI containing various content: a new technical article, product release notes, updates, technical musings from their applied scientists, etc. She doesn’t read them all but enjoys keeping up with what they’re doing.
Another year goes by.
Kate starts working as the lead engineer on a new product, and she happens to have a need for a model that’s really good at classifying grainy low-resolution imagery and can provide accurate classifications without requiring mountains of additional training data.
Kate goes to Perplexity and to ChatGPT and asks them to do research and provide suggestions for the best classifier models for low-resolution imagery and situations where there's very little training data.
Perplexity and ChatGPT come back with two or three options that are relevant and interesting. Because ProductAI has an excellent Product Marketing website and tons of discoverable content, it was one of the recommendations made by Perplexity.
Kate decides that instead of trying two or three options right now, she'll go ahead and try ProductAI because she already knows a lot about the company, she believes that talented people built their products, and because they have detailed documentation, quickstart guides, and a Python SDK.
Kate signs up for ProductAI using SSO via GitHub and starts implementing their latest model into her prototype. The onboarding experience is smooth, and she's up and running the same afternoon. She's impressed with how quickly she was able to integrate it and with how well their classifier works on her data.
The next day, Kate mentions ProductAI in her team’s standup. Two other engineers on her team have come across it before independently — one from a conference last year, another from a podcast.
Over the next five days, Kate receives two automated emails from ProductAI, which contain helpful information and onboarding tutorials. They're focused and valuable... without asking for anything in return.
A week after integrating ProductAI, Kate's manager asks for an update on the project. Kate demonstrates how well ProductAI's classifier is working, and her manager is impressed with the results and timeline.
Two weeks pass, and Kate receives an email from ProductAI indicating that her free trial is about to end. The email includes a link to their pricing page. Kate's pleased to see that ProductAI actually offers a "Basic" plan for individuals that accommodates a single contributor and up to 10,000 API calls to their model every month. But her team is going to need more than that, so she selects their "Pro" plan for $89/month plus an extra $10/month/contributor - she'll need four contributors, including herself. Kate gets out her Expensify card and commits to $129/month; she sends invites to three of her coworkers immediately.
Over the next year, as Kate's engineering team grows, they add another four seats to their license.
Kate's team regularly demos their work - including the value & effectiveness of ProductAI - at internal sprint reviews and on departmental demo days. More and more people at Kate's company see and hear about ProductAI.
Over the next couple of years, ProductAI becomes widely adopted by several Product and Engineering teams at Kate's company. Eventually, IT takes notice and decides that it's time to buy an Enterprise license.

This scenario likely sounds familiar to most readers. You've probably experienced this exact adoption journey firsthand at your workplace, regardless of the specific software involved.

BUT, believe it or not, I have found that MANY executives at tech companies do not understand it - they have never gone through this process themselves nor have they seen it happen.

They still believe that all business-use software is purchased through a years-long Direct Procurement workflow, including a lengthy down-select of well-known vendors. They're operating with a different mental model; an outdated model; a model in which individual consumers drive themselves to Best Buy and go home with a cardboard box containing a physical CD and a license key. That's the type of person that I'm hoping to get through to with this series of articles.

Let me ask you this: in the sequence described above, when would have been an effective time for someone in Sales or Customer Success at ProductAI to reach out to Kate? Dun da dun: not until the very end. Not until Kate has already done her own research, tried the product, and demonstrated to herself that it's valuable. Not until Kate is already a customer.

Here's the kicker: even then, that outreach is unnecessary. The BEST time to reach out to Kate is well after she's a paying customer. It's after several engineering teams at Kate's company have already sold themselves on the value proposition and are using it. It's during the internal adoption and growth stage. It's when you can have a conversation about the additional benefits and cost-effectiveness of ProductAI's "Enterprise" plan.

Alternatively, if the scenario above had gone differently and Kate wasn't satisfied, there are two other appropriate times to contact her:

If after signing up, she didn't follow through and integrate ProductAI at all. This is an indication that the documentation or onboarding workflow wasn't effective; i.e., even though Kate might've wanted to proceed, ProductAI didn't make it easy to do so, and she could probably use some support.
If after Kate's two-week trial, the API calls from Kate's account stopped, this is an indication that she was able to integrate and use ProductAI but that it wasn't valuable enough to pay for the "Pro" plan that she needed. This is a great time for Product (at ProductAI) to reach out to Kate because if/when the conversion rate from free trial to paid subscription is low, it usually means that the product's value isn't commensurate with its price; i.e., ProductAI is priced too high (compared to competitors, given its value prop) or it just isn't providing the value that your users expect.

The point of my example is to illustrate that the typical purchasing behavior of B2B SaaS users REQUIRES the first two things that I mentioned in the introduction:

A focused product marketing website.
A great product with a self-serve model.

Early-stage SaaS isn't successfully sold via traditional methods anymore.

It isn't "procured." It's discovered.

Collaboration: Product, Product Marketing, Sales

I get a knot in my stomach every time I hear any of the following: "Sales Qualified Lead," "Sales Enablement," "Hubspot," "Outreach," "Budget Owner," "Purchase Authority."

It portrays a long list of companies with "enriched data," including the titles, email addresses, and names of people that, ultimately, want nothing to do with you... or if they do, it's because they have a nightmarish problem that no product can help them with. But I digress.

The collaboration that I'm talking about between Sales, Product, and Product Marketing is simple: embed them all on the same team, include a full-time lead gen expert (so that you can generate enough interest to get good data), and use appropriate analytics tools to develop effective marketing funnels with robust metrics and conversion rates at every stage.

Tooling for Collaboration

One of the biggest mistakes that inexperienced [product & software] companies make is misunderstanding the use of analytics in the customer journey; often, this is evidenced via perverse implementations of Hubspot and an overreliance on it (and similar CRMs, e.g., Salesforce) while ignoring visitor and user interactions with our application(s).

An example of this is a Marketing-controlled workflow in which the use of HubSpot forms is regimented across the board in order to quote "preserve data integrity." Below is an egregious example of a HubSpot form being used to capture lead data for a free-trial signup.

It's a FULL-PAGE FORM with eight (8) required input fields (11 in total) and three (3) required T&C checkboxes.

Would you sign up for this product? I wouldn't.

A signup form like this creates a barrier to entry, has a terrible conversion rate, only converts users that you don't actually want, and doesn't benefit potential users. From a Product perspective, you get far fewer (or zero) free-trial subscribers, which means that you aren't able to get user analytics or the data that you need to improve your product, refine your messaging, or target the right market segments.

So, what is the purpose of a form like this? Why would any company be willing to put this in front of its website visitors? It's for themselves; it's so that they can put leads into an ill-contrived workflow in HubSpot that ultimately won't deliver results. It's due to: 1. a complete lack of understanding of how people buy SaaS, and 2. using a tool (Hubspot) in an inappropriate way.

Contrast the example above with how Supabase does it (below); creating an account requires two clicks in total, including the GitHub SSO modal when it pops up.

This is a signup form created by Engineering and Product. If I didn't already know that this was Supabase, I'd assume that it's an out-of-the-box integration with a third-party IdP (many look similar). It's simple and effective. Its goal is to CONVERT and onboard users because the important data and analytics come after visitors become users. Not before. In other words, metadata (name, company, phone number) isn't nearly as valuable as data derived from post-signup interactions with your application... all of which you can send to far better analytical tools than HubSpot. Get it?

If you capture lead information in a HubSpot form and move that contact/lead through a HubSpot workflow to track all of your interactions with them, then what you're doing is tracking YOUR interactions with that lead, which may be appropriate for Inside Sales at traditional and well-established Enterprise software companies but is NOT appropriate or effective for early-stage SaaS products. The blunder is that you are NOT prioritizing capturing USERS' interactions with your application.

Now you may think that because your product marketing pages are designed in HubSpot's CMS, you have robust analytics on your visitors. INCORRECT. You haven't captured most (or any) of the main touchpoints and important interactions that your visitors and users have with the product.

Marketing's traditional response to this problem is that we should use HubSpot for everything. For example: our knowledge base should also be in HubSpot, our product marketing sites should be created in HubSpot's CMS, our users should be in a HubSpot database, we should use HubSpot as a payment gateway, etc., the list goes on and on with inappropriate and ineffective uses of HubSpot.

The problem is that HubSpot acquired rather than built all of the features and functionality that supports this, and it's a hodgepodge of garbage that leads to a terrible user experience and a set of artificial constraints that hog-tie Product and Engineering.

But back to my main point: HubSpot is being used as a CRM to track the Sales team's interactions with leads (aka "Deals" in HubSpot). The funnel that they define is based on their own expectations and faulty assumptions about the product and customer journey that they can't fully understand until they have better tooling, analytics, and data.

What's the Solution?

First, you must realize that SaaS is complex and multiple tools are necessary in order to get the analytics that you need. You can't dumb down or reduce the customer journey to something that's easily modeled by a single tool. So, abandon HubSpot entirely and replace it with better tools. For CRM, use Attio,. If HubSpot has their hooks into you too deeply to abandon, then leverage their API to send data from Product-designed forms rather than having an overreliance on their WYSIWYG utilities.
Second, empower your Product and Engineering team to use -at their discretion- the tools and technologies that will provide the best user experience and performance for your application so that internal factors like "lead qualification" don't limit the value delivery of your product.
Third, implement analytics and event tracking on all deployed components of your product, including the application(s) themselves, product website, documentation, API, etc. To start, use Posthog, which is perhaps the most advanced and insightful product analytics tool ever created. It's also free (up to a substantial amount of use). I also recommend using Segment, Mixpanel, and Customer.io, Plausible, and Heap. Also, Loops is an awesome transactional email and onboarding workflow tool (with built-in analytics).
Fourth, ensure that EVERYBODY on your team has access to all of the tools above. This is critical because you want everybody (in all functions) to be looking at the same data and gaining the same insight from it.
Fifth, get together as a team on a regular cadence and review analytics that are coming in from all of your sources and product's touchpoints. Have whiteboarding sessions during your analytics reviews and map out the customer journey. This is important because every product is a bit different, and the ROI is often found by understanding the nuances. There's no one-size-fits-all approach. As you go along, and as you get more data on the customer journey, and as you understand your visitors and users at a deeper level, continue refining your cohorts and marketing funnels; create new events and conversions where they are necessary.
Sixth, work together as a team to define specific stages in the customer journey that outreach could be effective, and define what triggers or conditions at each of those points should be used in order to highlight an opportunity.
Seventh, automate all of the above.
Finally, continue refining and improving your analytics. Get your team together regularly to review how visitors and users are interacting with your website and product. Doing so helps Product Management build a better product, understand their users, and prioritize features on the roadmap. It helps Product Marketing create better long-form content and decide which cohorts are driving growth, which are engaged, and which need to be nurtured. It helps Sales understand when outreach will be effective, how they can optimize their timing, and how they can coordinate outreach campaigns for specific cohorts in concert with Product Marketing campaigns.

In Conclusion

Build an Outstanding Product Marketing Website

Your website should clearly communicate who your product is for and what problems it solves. Include clear pricing, descriptive feature lists, explainer videos, testimonials from real users, compelling case studies, real data (if applicable), your product roadmap, an AI Chat Assistant, interactive feature/benefit discovery panels, as well as links to your app’s documentation, API docs, support, blog, Discord, and much more. Remove all business jargon and speak directly to your target customer’s needs and pain points.

I’ll write an article dedicated to this topic in the near future because it is so important. For now, I’ll just say that your Product Marketing website MUST be specific to your PRODUCT, not your company. Your PRODUCT MUST HAVE ITS OWN IDENTITY, BRANDING, TARGETING, and POSITIONING.

People don’t buy your company; they buy products that happen to be created by your company.

Create Valuable, Discoverable Content

Create evergreen content that addresses the questions and challenges your target customers face. This content should be genuinely helpful whether or not someone buys your product. The goal is to build trust and establish your company as a thought leader in your space.

Blog posts, technical guides, industry research, and video tutorials should all be part of your content strategy. Make sure this content is SEO-optimized and easily discoverable through search engines, social media, and industry forums.

Develop Self-Serve Onboarding

Allow potential customers to try your product with minimal friction. Create clear documentation, helpful tutorials, and robust SDKs that make it easy for technical users to start using your product independently.

The easier it is for someone to validate your product's value on their own, the more qualified your sales leads will be.

Create Cross-Functional Product Teams with Dedicated Resources

Product, Product Marketing, and Sales should all be embedded and dedicated full-time resources on the same team so that they work together and:

Share analytics and dashboards tracking content engagement, trial signups, and product usage.
Collaborate during regular meetings to review & refine the customer journey, discuss which content is resonating with prospects, and analyze conversion metrics.
Identify stages and triggers in the customer journey that are optimal for outreach; create and automate effective campaigns.

The most successful SaaS companies understand that product marketing isn't just about creating fancy landing pages or writing blog posts – it's about creating a foundation that makes Inside Sales effective.

When Product Marketing is done right, it solves the timing problem I discussed in Part 1. Instead of hoping to catch prospects at the right moment, you create systems that allow prospects to discover and engage with your product on their own timeline. Then, when they're ready to buy, your Sales team is there to help them over the finish line.

Remember: If you don't have excellent product marketing, you don't have a product – at least not one that Inside Sales can effectively sell.

Postscript

I want to round out this article with a final example of the Customer Success model - Upwork. It's a great case study because it highlights a paradigm that you have likely encountered many times with other products.

My first experience with Upwork was in 2009 when it was called Elance (before Upwork acquired Elance and oDesk). A co-founder and I hired a six-person engineering team to build our web application. In the first week after submitting our job to Elance, we received 90+ applications; by the end of the second week, it was up to 140. We had to shut it off. We then spent four excruciating weeks going through the details of each application, interviewing candidates, and creating decision-matrix spreadsheets to facilitate the down-select. If you've used Upwork recently, you know that nothing's changed.

Upwork is smart. Thus, they didn't fix the problem; rather, they leveraged it. If you create an account on Upwork using your work email (i.e. not *@gmail.com) and you verify your payment method, an Enterprise Sales Representative will reach out to you to schedule a call and discuss your needs. What they offer is a value-added service in which you can sign up for a couple of different Enterprise plans (starting at $1,000 per month). They'll source pre-vetted, highly qualified candidates meeting the criteria that you specify. The advantage is that you don't have to spend hundreds of hours screening applicants and interviewing people who have performed identity fraud and aren't who they say they are.

The point here is that Upwork is using a Customer Success model to deploy their sales resources at the most opportune time—when they already have a client that has a specific need for their product. Granted, this example is more related to the Part 1 article, but I wanted to include it here anyway. Moreover, it demonstrates that the Customer Success model can be very effective for products in various stages of maturity.

Photo by Jason Goodman on Unsplash