BUILD VS BUY: Invest in a Revenue Acceleration Platform or build your own?

If you’re a marketing or sales leader, you may be facing the build vs. buy dilemma when deciding how to measure and optimize pipeline generation and revenue. Whether you’re trying to make sense of click data from LinkedIn ads or mapping out the buyer’s journey, the decision to build an in-house solution or buy a pre-built one like HockeyStack can be pivotal. Let’s dive into this conversation and unpack what’s really at stake.

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When Building In-House Makes Sense

At first glance, building your own revenue analytics system might seem appealing. You get full control and can tailor everything to your specific needs. But is it always worth it?

Consider building if:

• You just need a visualization layer on top of your CRM. Business Intelligence (BI) tools might suffice here.
• You’re confident in your data quality. If you trust your existing data and feel comfortable making decisions based on it, building could work.
• Your team isn’t concerned about capturing and measuring anonymous interactions as part of the buyer’s journey.

Building your own basic solution in house is possible with these steps:

1. Map out all your tools and KPIs

Step 1: Map out your tech stack and align on KPIs with the relevant stakeholders.

Step 2: Determine what’s really important for your business. Typical questions to understand this are things like:

• How can marketing support revenue?
• What does the leadership care about?

Step 3: Determine what metrics each platform needs to bring to your Master Dashboard. Ensure you know where revenue metrics, form submissions, and cost will come from.

2. Bring all your data into a central spreadsheet or BI tool (aka your Master Dashboard)

At this stage, BI tools and spreadsheets are a great way to get started and get some visibility.

3. Build your first attribution models starting with First/Last touch

There are limitations on what you will be able to understand in doing this, but it is still the best way to start if you don’t have anything else set up.

Once you build these two attribution models, you can look at brand awareness channels/campaigns with first touch and conversion points with last touch.

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‍4. Calculate your Blended CAC

Import your advertising, event spend, tool spend, headcount spend data into the same spreadsheet or BI tool.

From there, take the spend for a given period and divide it by the last touch attributed or first touch attributed number.

This will give you a result that is either weighted towards the very top of the funnel or the very bottom — but it is better than having no cost discipline.

Considerations during your preparation phase:

• Time commitment: You’re looking at roughly 200 hours of engineering time, plus an additional 20-30 hours of feedback from marketing. That’s a big lift.
• Expertise: You’ll need frontend, database, and data engineers. This isn’t just a plug-and-play scenario.
• Ongoing maintenance: Building a tool isn’t a one-and-done. You’ll need to keep refining, testing, and deploying to ensure it stays usable.

Reminders:

• Have a plan for reporting during the build phase. If you rely on in-house engineers or operations team members to build a solution, they may be slower with ongoing reporting asks.
• Don’t forget to train your team on the new solution to get the most out of the effort! Everyone who cares about the data should understand your models and how to interpret them.

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Buying a Solution: When HockeyStack is a Game Changer

Now let’s talk about buying a pre-built solution like HockeyStack. What’s the upside?

HockeyStack takes a lot of the pain out of the equation by offering a no-code, plug-and-play platform. What sets it apart is its ability to help you not just answer what’s happening, but also why it’s happening. This isn’t just a data aggregation tool—it’s a way to make strategic decisions.

Here’s why buying might be better:

• Data breadth: HockeyStack pulls in everything from impression-level data to conversion data, to pipeline and closed won deal amounts, giving you a holistic view of marketing efforts on revenue.
• Data cleanliness: Even if your data is a bit messy, HockeyStack can help you make sense of it without waiting for a big cleanup project.
• Eliminate manual work: No more pulling exports from LinkedIn, Google Ads, or other platforms, then manually stitching them together for reports.
• No-code insights: Say goodbye to constant requests for reports from your RevOps or data team. HockeyStack’s intuitive reporting tool allows your team to generate insights themselves.
• Anonymous user activity aggregated: Lots of members of the buying committee might be poking around the website, but will never fill out a form. With HockeyStack, you can see the full buyer’s journey complete with anonymous visits, aggregated at the account level. 

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So what are the top reasons HockeyStack customers decided not to build an in-house solution?

Lack of Data

Much of the buyer journey is done through anonymous web activity, things like:

• ad impressions and engagements
• brand awareness campaigns that are built for reach, not clicks or form fills
• visits to third-party review sites like G2 

Internal builds can only track events that led to conversion (form fills). But as mentioned above, many touchpoints are anonymous website visits and other engagements from users who have yet to convert on the website.

• Example: One person converts on the website to book a call, but there can be up to 10 different contacts at the account visiting your website and engaging with your brand for months or years prior. This is data you need visibility into to make correct decisions for your marketing strategy.

In addition, most builds can only drill one level down into the channel or campaign.

Teams that bought HockeyStack wanted to be able to see specific ads, content, and assets to understand how each was impacting pipeline.

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Finally, website data can only be tracked in internal builds via Marketing Automation (no pre-conversion data) or Web Analytics tools like GA4, which don’t match to account and don’t show how website engagement ties to pipeline and revenue.  

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Quality of Models/Reporting

If you are building internally, because of the inability to track anonymous activity or tie pre-form fill activity to contacts, reporting will be based on First or Last Touch. These attribution models are great for a single lens (when, where and why do contacts convert), but they miss dozens to hundreds of other touchpoints that occur in the buyer journey before the first form fill.

More advanced setups have multi-touch models, but they are based on campaign association (if an SFDC campaign member is associated with the opportunity).  Even with this limitation, to be usable for analysis, it still requires:

• All trackable touchpoints to be categorized as a campaign, and it still misses all top-of-funnel touchpoints
• All contacts to be associated with the campaign/opportunities, which misses prospects who have yet to convert

The most effective way to understand marketing’s impact is to track as much data as possible and use different measurement methods depending on the questions being asked. Teams should regularly use first-touch, last-touch, and multi-touch models, as well as lift and incrementality reports.   Even if you built out a full set of multi-touch models, they are strictly correlational in nature, and do not demonstrate causality. 

To make confident, data-backed decisions, this directional data needs to be verified by lift reports (cohort comparison) that the touchpoint or campaign does impact conversion. 

Constructing these models internally requires dedicated engineering resources, specific requirements and the ability to build these models on top of your visualization tool.

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Self-Service

Marketing teams should be able to access relevant data and spin up reports in real time to answer questions as they come up.

For example, teams should easily be able to slice and dice the data as they please based on:

• Activity
• Geography
• Region
• Product
• Business Unit
• Company Sizes
• Vertical or Industry

Building internally will likely limit data exploration to technical users if the tool is code-based and doesn’t have a user-friendly UI. If your team will need to put in a request for minor or major changes, the overhead of the in-house tool is simply creating another bottleneck. 

To gain insights quickly and efficiently, every member of your team should be able to create reports in real time.

Resources

Internal builds take a massive amount of resources to build and maintain (estimate 7-10 months), and even the best builds are missing most of the buyer journey.  The main reasons it is so difficult to build and maintain internally are:

• All data integrations need to be configured and maintained, i.e. CRM, Ad Networks, Review Sites, Marketing Automation Tools, CRM
• Usually, only a couple of people know how the setup works, so if someone leaves, the setup and functionality may leave with them
• To avoid the problem above, consistent documentation needs to be assigned to the owner or creators of the tool

Many teams feel they can build a solution like this internally because of their experiences with traditional attribution tools. But traditional attribution tools are based on a similar data set to internal builds as many rely on post-conversion data, converted contacts, and don’t include impression or engagement data either. 

To actually advance insights into what’s working and what’s not, marketing and sales teams should be able to outsource reporting infrastructure and spend time drawing conclusions.

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The Bottom Line: Time is Money

There are some obvious questions to ask yourself before embarking on an in-house build:

• Can you clean up your data while building your internal solution?
• How will you report until the solution is fully operational?
• What’s the potential revenue impact if you had a working solution right now vs. in 6 months?

If you’re working on tight timelines (which, let’s face it, most marketers are), buying HockeyStack could mean the difference between hitting your goals this quarter or missing them because you’re waiting on a solution that’s still in development.

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Final Thoughts: What’s the Right Choice for You?

If understanding the “why” behind your customer’s actions is key to your strategy, and if you want a solution that combines ease-of-use with depth of insights, then HockeyStack is the way to go. But if you’ve got a simpler need, rock-solid data, and plenty of engineering bandwidth, an in-house solution might be a fit.

Whatever path you choose, the key is making a decision that aligns with both your short-term needs and long-term vision.

What’s your next move—build or buy?  If you’re leaning towards buy, book a demo with our team or play with the interactive demo.

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