Prism Consulting

05/11/2026

Tennessee weather is on point today!

Took the laptop outside as I focus on building the business and work on client work. 🤠

03/20/2026

𝗦𝗘𝗢 𝗶𝗻 𝟮𝟬𝟮𝟲: 𝗠𝗼𝘀𝘁 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀𝗲𝘀 𝗮𝗿𝗲 𝗺𝗲𝗮𝘀𝘂𝗿𝗶𝗻𝗴 𝗶𝘁 𝘄𝗿𝗼𝗻𝗴

I had a conversation recently about how to measure SEO and hold teams accountable.

It’s harder than it used to be.

SEO is shaped by platforms that constantly change algorithms, don’t fully explain how they work, and ultimately profit from ads. Outcomes also vary based on your business model.

So it’s not surprising most businesses measure SEO incorrectly.

𝗧𝗵𝗲 𝗠𝗲𝗮𝘀𝘂𝗿𝗲𝗺𝗲𝗻𝘁 𝗥𝗲𝘀𝗲𝘁

SEO used to be simple:

Rankings → Traffic → Leads

That model is breaking.

Search behavior has shifted:

* more zero-click results
* more AI-generated answers
* less reliance on clicks

This isn’t just a traffic issue.
It’s a measurement issue.

𝗧𝗵𝗲 𝗥𝗲𝗮𝗹 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻

Most teams track rankings, traffic, and impressions.

Those are useful, but not the scoreboard.

👉 Is SEO actually driving business outcomes?

𝗪𝗵𝗮𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 𝗠𝗼𝗿𝗲

A better KPI set:

* Organic leads
* Lead → customer conversion rate
* Revenue influenced by organic
* CPA vs paid
* Visibility in real buying searches
* Reviews and trust signals

𝗪𝗵𝗲𝗿𝗲 𝗜𝘁 𝗕𝗿𝗲𝗮𝗸𝘀: 𝗔𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻

SEO doesn’t work alone.

A user might click a paid ad, come back via organic, then convert.

If you isolate SEO, you misattribute performance.

Organic often reinforces and closes demand.

𝗧𝗵𝗲 𝗣𝗼𝘄𝗲𝗿 𝗮𝗻𝗱 𝗥𝗶𝘀𝗸

SEO can create predictable growth through consistent traffic and conversion.

But it also carries risk. Algorithm changes can shift performance quickly.

𝗧𝗵𝗲 𝗕𝗶𝗴𝗴𝗲𝗿 𝗦𝘆𝘀𝘁𝗲𝗺

Running ads without SEO weakens ads.
Running SEO without ads slows growth.

The strongest companies do both.

That creates momentum, and momentum drives visibility.

𝗙𝗶𝗻𝗮𝗹 𝗧𝗵𝗼𝘂𝗴𝗵𝘁

SEO is no longer about activity.

It’s about performance within a system.

Most teams will keep reporting rankings.

The best ones will measure what actually drives revenue.

03/17/2026

One of the biggest surprises in my career working in marketing analytics and data has been how many companies are incredibly busy but not actually operating with clear, trusted data.

Over the years I have stepped into several different types of situations.

Sometimes the company already had dashboards and reports in place. On the surface everything looked good. But once we started digging in, some of the numbers were wrong or disconnected from the CRM. Attribution did not line up. Leadership was making decisions off reports that were not actually reliable.

Other times the problem was more foundational. The business was growing and everyone was working hard, but the organization was not operating with clearly defined KPIs yet. There was a lot of activity, but limited visibility into what was actually driving performance.

And in some cases the company simply needed the foundation built first. Descriptive analytics. Clear reporting. Shared definitions. A baseline understanding of what was happening in the business.

Only after that work was done could the more advanced analytics happen. Forecasting. Modeling. Deeper strategic insights.

Across all of these situations, the pattern is usually the same.

Companies are busy. Teams are working hard. But the data systems underneath the business are not always structured in a way that leadership can confidently trust.

Good analytics is not just about dashboards.

It is about helping organizations reach the point where leaders can confidently look at the numbers and make decisions based on them.

Much of my work has focused on helping companies move from:

Activity → clarity
Reports → trusted insight
Data → confident decisions

Curious to hear from others working in RevOps, analytics, or leadership roles.

What data challenges have you most often seen inside organizations?

03/14/2026

Will AI replace Data Scientists?

Not at all. But AI will change how data science work gets done.

One of the biggest issues organizations face today is not a lack of tools. It is a lack of good questions.

There is often a large gap between business stakeholders and the ability to translate a business problem into a clear analytical question. AI systems can generate answers quickly, but they frequently respond in ways that align with what people want to hear.

That can unintentionally reinforce assumptions, inflate executive confidence, and lead to poor business decisions.

This is where real data science still matters.

Data science is fundamentally about applying the scientific method to business problems:

1. Define the right question
2. Form hypotheses
3. Gather and validate data
4. Test assumptions
5. Interpret results in context
6. Repeat with more refined questions

AI is incredibly valuable in this process. It accelerates many parts of the workflow:

• Quickly answering low-hanging fruit questions
• Enabling self-service analytics for simple requests
• Speeding up model development and analysis
• Reducing time spent on repetitive analyst tasks

In other words, AI dramatically improves speed to analysis.

But identifying the right problem to solve and interpreting results responsibly still requires human judgment, domain expertise, and critical thinking.

The organizations that win with AI will not be the ones that replace data scientists.

They will be the ones that combine AI speed with human reasoning and strong analytical methodology.

03/13/2026

Most companies are not struggling because they lack data.
They are struggling because their data is fragmented, delayed, or unclear.

Across the case studies on our website, the same core problems show up again and again:

• Leadership teams flying blind without reliable revenue dashboards
• Marketing and sales arguing over whose numbers are correct
• Reporting processes taking hours every week and still lacking trust
• Data scattered across platforms like CRMs, ad platforms, and analytics tools
• Teams making decisions based on gut feel instead of clear metrics

These companies did not need more tools. They needed clarity.

By rebuilding their reporting infrastructure, integrating their systems, and creating executive-level dashboards, we helped them:

• Align sales, marketing, and leadership around the same numbers
• Replace manual reporting with automated dashboards
• Surface the metrics that actually drive growth
• Turn daily reporting into a decision-making system for the whole team

The result is simpler operations, faster decisions, and teams that finally trust their data.

If any of those challenges sound familiar, the full case studies are available here:
https://prismco.us/case-studies

They show exactly how these problems were solved and what changed afterward.

03/11/2026

Most teams are flying blind when it comes to daily performance.

Sales sees one set of numbers.
Marketing sees another.
Leadership is trying to piece it all together.

That is exactly the problem this Daily Scorecard Dashboard solved for one organization.

Every morning the entire team reviews the same scorecard. It tracks the metrics that actually drive the business: sales performance, marketing activity, revenue pacing, operational KPIs, and progress toward goals.

Instead of waiting for monthly reports or debating whose spreadsheet is correct, everyone sees the same truth in one place.

The impact was immediate:

• Sales and marketing started working from the same data
• Leadership could quickly identify what was working and what was not
• The team began making faster, data-driven decisions
• Accountability and alignment improved across departments

One of the leaders described it perfectly:

“I come into work and really look forward to viewing the Daily Scorecard dashboard. It's like reading a newspaper. It's fun to see, creates unity among the entire team seeing it daily each morning, spurs questions, leads to great data driven decisions, and is extremely effective for helping us hit our goals.” -Jim

This is what happens when data stops being scattered across systems and starts becoming a daily operating system for the business.

When sales, marketing, and leadership are looking at the same numbers every day, alignment happens naturally.

That is the power of Revenue Clarity.

If your team is still waiting for end-of-month reports to understand performance, it may be time to rethink your data infrastructure.

Prism Consulting helps organizations turn scattered data into clear dashboards that drive smarter decisions every day.

If you want to see what this could look like for your company, comment DATA or send a message.

03/11/2026

This is for you!

God doesn’t write defeat into the story of those who trust Him. What looked like a full stop was only a comma in the divine sentence. The Author is still writing, the promise is still alive, and your story is not finished yet.
—

03/10/2026

Why Last-Click Attribution Is Costing You Money...

A customer sees your LinkedIn post. Then a retargeting ad. Then reads a case study. Then searches your name and clicks a Google ad. Then buys.

Under last-click attribution, Google gets 100% of the credit.

LinkedIn, retargeting, and content get zero.

So next quarter, you cut the "underperforming" channels - and wonder why revenue drops.

Last-click attribution does not just misrepresent your marketing. It actively misdirects your budget toward the wrong places. Good channels get starved. Bad channels get funded. And the cycle continues.

✅Multi-touch attribution is not a luxury for enterprise companies. It is a survival requirement for any business serious about scaling.

I've see that exact thing happen and how the leaders have their gut feelings that those 'last-click attribution' reports weren't accurate, or how the other reports don't match (The LinkedIn metrics show positive results, the Retargeting Ads show positive results, the case study shows positive results, and Google Ads show positive results). But attributing the revenue to each one of those doesn't match the investments poured into those efforts, and it's just plain confusing. Deciding which attribution model is best depends on the business and decisions to make, but usually data-driven multi-touch or custom attribution models (or marketing mix modeling) is best to help drive to clarity and enable scale!

--
Last-click attribution is quietly misallocating your budget right now. I help companies rebuild attribution the right way in 90 days. If that's relevant, let's connect.

03/08/2026

Prism Consulting’s website just got a major update!

The goal was simple: clearly explain the problem many growing companies face but struggle to articulate.

Most organizations today have plenty of data.

They have dashboards, marketing platforms, CRM systems, and analytics tools.

What they often lack is clarity about what is actually driving revenue.

The updated site explains how Prism approaches that challenge through:

• Revenue visibility and attribution
• Marketing and sales performance dashboards
• Data strategy and analytics infrastructure
• Clear systems leadership teams can use to make decisions

If you work in marketing leadership, RevOps, or analytics and have ever asked:

“Why do all our dashboards tell a different story?”

You will probably recognize the problem we are solving.

Take a look: https://prismco.us

Feedback is always welcome as the platform continues to evolve!

05/26/2025

Remembering and honoring.