To analyze your marketing data following the SUMAS framework, begin by understanding your (S) strategy. This involves identifying key aspects of your company, customers, and competition.; define your (U) use cases between client reporting or performance management; map your (M) metrics between conversion, engagement, and visibility; (A) add context by comparing your data vs goals, time, rates, budgets, and benchmarks; and finally, (S) segment your data all the way down from product to channels, campaigns, audiences, or creatives.

In this tutorial, you’ll learn to analyze your marketing data with our proposed framework (SUMAS) to help you develop clarity and consistency to measure your marketing performance towards business outcomes, across teams or agencies, SMBs or enteprise, or even across industries and channels.

The SUMAS framework we propose has five elements:

1. Strategy
2. Use cases
3. Metrics
4. Add context
5. Segments

We made it an acronym so it’s easier to remember 😉. SUMAS means “sums” in Spanish*

Strategy

The first step is to have clarity of your business strategy by doing a situation analysis to know your playing field, , and we’ll use the 3 C’s model to understand a company beyond its performance marketing data.

• Company: business model, product, pricing, revenue, unit economics, team, budget, and other available data that represents the current state of the company.
• Customer: ICP profile, pain points, objections, and jobs to be done.
• Competitors: alternatives to your products within and outside your category and segment.

Also, analyze the intersections among these three elements:

• Go-to market strategy (company & customers): know how the company gets customers.
• Competitive advantage (Company & competitors): value proposition, differentiation, defensibility, and weaknesses.
• Opportunities and threats (customers and competitors): market trends. These are variables you can’t control.

Finally, define your positioning, which represents your solution, to whom you sell it, and what makes you different, representing the intersection of company, customers, and competitors.

In a nutshell, to understand the company you’ll work with—whreas your employer or client—you need to answer these 7 questions:

1. What you do and how you make money?
2. To whom we’re selling to?
3. What are our alternatives?
4. How do we get customers?
5. What makes us different?
6. What’s going on in the market?
7. As a result, what is our positioning?

Use cases

Use cases are the solution of a problem for a user.

Use cases are the starting point of a marketing or growth activity (or analysis).

Thinking of use cases first before tools and technology gets you closer to truly delivering value because you’ll change the narrative from APIs, pipelines, and dashboards to funnels, ROI calculators, OKRs, and KPIs

Marketing data analysis use cases

Marketing dashboards, reports, or any sort of analysis work as a feedback system meant to influence your and your team’s behavior.

You analyze data to go faster. Speed is doing the right things fast. You use data to make the right decisions and to influence people to do things.

You analyze marketing data to answer questions, monitor performance, and influence managers and clients.

Answering questions

You’re likely to create ad-hoc analysis for your daily operations and decisions. Simply researching keywords, managing budgets on your ad campaigns, checkingn best-performing questions, are part of the daily activities that involve some data analysis.

Performance monitoring

Tracking and comparing your performance over time through KPIs, towards objectives.

We monitor performance to have a notion of feedback on our actions. An ascending or descending line-chart, or a green or red scorecard derive in positive or—more often—negative reinforcement.

Such feedback helps teams align their tasks, efforts, and priorities towards hitting goals, measured through KPIs.

Influence managers and clients

You create dashboards and reports to show your work or progress to your team or clients if you’re an agency, generally with a weekly or monthly cadence.

These presentations, unlike performance monitoring, aren’t meant to analyze data but to present it through storytelling; you tie your data to a cohesive narrative that will help you influence and inform your team or clients.

In that sense, I’d say these data presentations are similar to sales pitches backed by data.

The outcome of these presentations is to provide clarity and, hopefully, influence your audience to agree with your recommendations.

Yet, don’t confuse influencing with persuading: influencing is about aligning everyone to the best possible outcome; persuading is about biasing an audience towards your desires and preferences.

Don’t use data presentations to make you look better (when not deserved) or present misleading data to shift the narrative of a negative outcome into a positive one.

Users and frequency

To define your use cases, you should consider your audience and the frequency of analysis.

• Hourly, daily: ad-hoc, operational questions (e.g. ad pacing analysis)
• Weekly, monthly: client/team presentations (weekly performance monitoring)
• Quarterly, annual: marketing plans, budgeting (ads or SEO audits)

Define your metrics

To set and prioritize metrics, we’ll use funnels, driver trees, and money maps.

Funnels

Funnels help marketers understand the buying process steps by breaking them down into conversion, engagement, and visibility.

• Visibility: users see your content (e.g. impressions, reach, traffic, followers)
• Engagement: users interact with your content (e,g. clicks, engagements)
• Conversion: users do a desired business outcome (e.g. purchases, leads)

In this step, you may define several metrics for every funnel stage, but ultimately pick 1 or 2 to focus on. You can refer to the metrics you prioritize as your KPIs.

Driver trees

Driver trees, on the other hand, let us map and break down our results into actionable items (aka leading and lagging indicators, or input and output metrics).

Lagging indicators such as conversions represent the output or results of our marketing efforts.

We can influence them, but don’t have full control on them. They’re our north star metrics, but alone they’re not actionable.

Leading indicators are the inputs that we can control that help us influence our outcomes. Our challenge as marketers is to correctly identifying them; it’s an exception rather than a rule that inputs linearly translate into ouputs.

Prioritization matrix

Money maps are a prioritization tool to help you identify the activities with the potential highgest impact and lower effort based on the user’s intent: the closer is an activity to the conversion, the easier it is to execute and the higher it’s impact.

We’ll use moeny maps to prioritize the metrics we’ll influence so we can come up with an action plan for our team or clients.

While marketing data is tracked on dashboards, marketing execution is tracked on your productivity tools which ultimately lead to influence your metrics.

To build your money map, break down your current and planned marketing initiatives into the funnel stages (e.g. visibility, engagement, conversion).

Then, tag those activities as:

• Not working
• Kind of working
• Working

You may prioritize the activitities that are kind of working as they are your long-hanging fruits; improving what’s working might lead to marginal improvements, and focusing on what’s not working is harder.

Yet, still consider these factors when it comes to prioritizing your marketing activities:

1. Feedback and gut: your experience,industry knowledge, and knowing your clients may influence your prioritization the most.
2. Delivering value: while not close to the conversion, marketing activities meant to directly deliver value to your customers are worth prioritizing.
3. Effort: finding activities that are easy to execute, you’re especially good at, or do not need delegation are worth considering.
4. Measurability: most marketers might prioritize marketing activities based on their capacity to measure their outcome (such as ads)as they provide consistent, on-going feedback and helps managing stakeholders’ expectations. At the same time, don’t trade off delivering value for the sake of measurability.
5. Differentiation: consider channels and tactics that are still not saturated; you’re trading off certainty with lower costs of acquisition. An example are the lower CPMs of raising social media platforms, such as the early days of Google and Facebook, or TikTok nowadays.
6. Defensibility: consider long-term initiatives that will become hard to copy by competitors.
7. Scalability: find activities that have the potential to compound and scale over time, or in other words, activities that give you greater returns over time without you putting more effort.

Add context

To make your marketing data meaningful and actionable, compare it with goals, time, rates, budget, and benchmarks to add context.

Goals

Compare wtih your business goals and OKRs. Marketing goals are linked to revenue and defined b previously discussed strategy elements: industry, Go-to market, and unit economics such as Payback period and CLTV).

Time

Compare your performance data over time such as hourly, daily, weekly, monthly, quarterly, or annually.

Time ranges are determined by the feedback frequency of your marketing effort and if the scope of your analysis is operational, tactical, analytical, or strategic.

• Programmatic advertising on large-scale budgets, or special dates such as Black Friday might require hourly, or even real-time analysis (operational).
• Channels such as SEO that may have slow feedback are worth tracking weekly. Your changes won’t be reflected in hours but in days, weeks, or even months, depending on factors as your website authority and Google algorithm’s updates.
• Team or client meetings happen generally on a weekly or monthly cadence for performance review (tactical).
• Media planning, channel analysis, setting and tracking global KPIs, or in general refining go-to market, tend to happen on a monthly, quarterly, or annual basis (strategic).

Rates

‘Rate’ metrics measure effectiveness to generate an action (output) compared to an audience (input), with names varying by channel, such as:

• CTR (Click-through rates) represent the effectiveness of ads to turn impressions or reach into clicks.
• Open rate represents the effectiveness of emails delivered to be opened.
• Engagement rate represents the effectiveness of social media posts to turn impressions into engagements.
• Conversion rate represent the effectiveness of a website to turn sessions or users into conversions or clients.

Budget

The most telling way to communicate your marketing data is comparing your marketing metrics with a budget or with business value.

Compare desired actions such as impressions, clicks, engagements, or conversions with actual spend or business value generated, such as:

• Cost per a thousand (Mille) Impressions (CPM): divide ad spend by 1000 impressions to know the average cost of visibility.
• Cost per Click (CPC): divide ad spend by click to know the average cost per engagement.
• Cost per Acquisition (CPA): divide ad spend by acquisition (e.g. leads, purchases), to know the cost per conversion.
• ROAS (Return on ad spend): divide ad spend by revenue to know the average money that you return for every $1 on ad spend.

All these budget-related metrics divide ad spend by a visibility, engagement, or conversion action to know the average to get one of them.

Benchmarks

As a final comparison, you might compare your peformance data against industry benchmarks to have a notion on how your marketing stacks up with similar companies.

Some useful benchmark sources are:

• The Google Ads Keyword Planner
• Social Media Competitive Intelligence tools
• Databox Benchmarks tool

Segment

Breaking down your marketing data helps you tell what segments are driving your performance—and where you need to focus.

Ways to segment your marketing data

You may segment your marketing data by the following criteria:

1. Campaign: break down by your marketing campaign names.
2. Business: break down data by client, if you’re an agency, or by product or service, if you’re a company.
3. Channel: break down by medium (SEO, Ads, Social) and source (Facebook Ads, Google Ads, TikTok Ads, etc.).
4. Objective: break down by objective type such as conversion, engagement, visibility, o even more specifically, awareness, expansion, recovery, churn prevention, upsells, downsales, etc.
5. Audience: break down by interests, behaviors, demographics, geography, placements, and technology.
6. Content: break down by topic, format, creative, hashtag, keyword, post.
7. Time: hour, date, day of week, week, month, quarter, year

Breaking down by campaign is the most common segmentation criteria as it encompasses all the other ones.

A marketing campaign is the set of marketing activities meant to reach a goal for a particular business by reaching a specific audience with content through certain channels.

Segmentation prioritization

To make your analysis more simple, make sure to sort your segmentation criteria as a “cascade”, starting with the criteria with less segments all the way down to the ones with more.

For instance:

• If you’re promoting a few products through multiple channels, break down first by product, and then by channel.
• If you’re promoting multiple products through a few channels, break down first by channel and then by product.

To do this analysis effectively, these segmentation criteria should be consistenly reflected in your accounts, campaigns, and content names, titles, copy, or hashtags, as well as your URLs and UTM parameters.

Not standardizing your marketing asset naming (aka taxonomy or name convention) when starting out, while seems like a small mistake, leads to an annoying inability to segment your data correctly.

Yet, there’s a small mistake that becomes pretty annoying over time: most marketing teams don’t have a standardized taxonomy (aka naming conventions) for their marketing assets, affecting their ability to eventually segment their data.

For instance:

• Using “FB”, “facebook”, or “meta” on your UTM paramters on your Facebook Ads campaigns.
• Having dozens or hundreds of URLs on your website without subfolders that reflect herarchy (which might also indirectly affect your SEO performance).
• Not using hashtags consistently on your Social Media posts.

Sounds familiar? To solve it you can:

• Document and standardize your marketing assets naming (with our UTM builder template) for now and the future.
• Changing your historical data (e.g. changing your campaigns names)
• Changing your URLs, or editing your content, but altering your marketing data might mess your reporting tools such as GA4 or Search Console

The bottom-line

The objective of marketing is to efficiently acquire customers and generate revenue. Key performance indicators include overall, bottom-line metrics like CAC, LTV, Retention, Payback, ROAS, MER, and contribution margins.

While measuring bottom-line metrics is useful, seeking Return on Investment on every single marketing activity may bias you towards risk-averse strategies, favoring undifferentiated activities in saturated channels like Google Ads.

This approach may lead to predictable outcomes (predictably costly, too).

Instead, we propose monitoring business indicators as outputs, emphasizing control over visibility, engagement, and conversion metrics. Prioritizing these inputs enables a focus on delivering value to users, even when attribution measurement is challenging.