Can MMM measure branded vs. non-branded search?

Every fan at a sold-out stadium walks past a ticket-taker at the gate. If you judged the season by who scanned the most tickets, the ticket-taker would look like the reason the stands were full. The team, the rivalry, and a winning streak filled those seats. The gate is just where the result of all of those factors gets counted.

Branded search sits at the same gate. By the time someone types your brand name into Google, something else has usually already convinced them. So, can a marketing mix model (MMM) measure branded and non-branded search separately to tease out this relationship? Yes, it can, but only if the model understands that the two do different jobs: non-branded search tends to help people discover you, while branded search mostly captures people who already know you. Many traditional MMMs don't make that distinction, so they hand branded search credit for demand other campaigns created.

That matters because branded search budgets are some of the most argued-over dollars in marketing. If your measurement overstates them, you'll keep paying for clicks that would've happened anyway while trimming the campaigns that sent people to search in the first place.

Key takeaways

• Yes, an MMM can measure branded and non-branded search separately, as long as it accounts for the different roles they play.
• Branded search mostly captures demand that already exists, while non-branded search, video, and social tend to create new demand.
• Google Ads and last-click reporting show very high returns for branded search because people searching your brand name were already likely to buy.
• Traditional MMMs often repeat that mistake, because branded search spend rises at the same time as brand awareness and seasonal demand.
• Prescient's MMM, OMEN, models demand creation and demand capture differently, so campaigns that drive people to search for your brand get credit through halo effects.
• Measuring search this way helps teams find where branded search stops paying off and move that budget to campaigns that grow demand.

Branded search looks like your best channel, and that's the problem

Most growth teams have had the same argument more than once: is branded search driving revenue, or are you paying for clicks from people who were going to buy anyway? It's a fair question, and platform reporting makes it harder to answer.

Google Ads typically reports very high ROAS for branded search. That's not surprising, since someone searching your exact brand name has already decided they're interested. Last-click reporting then gives that search all the credit for the sale, even when a YouTube ad, a creator video, or a CTV spot is what put your name in their head.

You'd hope an MMM would correct that. Traditional MMMs often confirm it instead, reporting huge efficiency for branded search and recommending more budget for brand keywords while cutting the video and awareness campaigns that generate those searches. The cost runs in two directions: you overspend defending your own brand terms, and you starve the campaigns that create the searches.

Why traditional MMMs get search wrong

Traditional MMMs misread search for three reasons: they treat every channel as an independent source of sales, they have no sense of which campaigns create demand, and they can't tell branded and non-branded search apart when the two rise together.

Every channel is treated as its own source of sales

A traditional MMM typically explains sales as a baseline plus separate contributions from branded search, non-branded search, YouTube, and every other channel. Branded search spend and conversions climb at the same time brand awareness grows or seasonal demand surges. A model built from independent pieces can read that timing as branded search doing the work, and it hands branded search credit that belongs to whatever created the demand.

There's no sense of what happened first

Traditional models don't represent sequence or the flow of demand from one channel to another. They can't account for the fact that a CTV ad or a TikTok video led someone to search your brand name three days later. Without that, the upper-funnel campaign gets no credit for the search it caused.

Branded and non-branded search move together

Non-branded campaigns, such as "best running shoes," and branded campaigns, such as "[YourBrand] running shoes," tend to scale up together during promotions. When two inputs rise and fall in step, a traditional model can't reliably tell their effects apart, so their estimated returns can swing widely or flip from one run to the next.

How Prescient measures branded and non-branded search

Prescient measures search by modeling which campaigns create demand and which ones capture it, within one connected system where demand builds over time. Our model works backward from what can be observed—your spend by campaign and your sales—to estimate what drove those sales, and it doesn't rely on tracking individual searchers. (We have branded search FAQs about our model specifically if you want to dive in there first.)

Demand creation and demand capture are modeled differently

Our model represents the difference between campaigns that build demand and campaigns that convert it. Prescient separates branded search, which often captures existing demand, from non-branded search, shopping, and display, which generate new demand. Upper-funnel video and social sit on the demand-creation side as well. Because branded search is treated as a way to capture demand that already exists, it can't claim credit for creating that demand.

Campaigns that drive searches get credit through halo effects

When a YouTube campaign or a non-branded search campaign introduces someone to your brand, some of that interest shows up later as branded searches. Prescient measures this as a halo effect, the revenue a campaign drives indirectly through another channel, and credits it to the campaign that created the interest. Upper-funnel campaigns tend to produce the most halo effects, though any campaign can.

Branded search can show saturation when it hits a ceiling

Branded search has a natural limit: you can only buy clicks on searches that people actually make. Once you're already showing up for most of those searches, more spend doesn't create more of them. Our model doesn't force every campaign onto the same fixed curve, so a branded search campaign that has run into that ceiling can show diminishing returns, while a non-branded campaign with room to grow can keep a steadier response.

What affects how clearly an MMM can read search

An MMM reads search most clearly when it has campaign-level data and enough variation in spend to tell campaigns apart. Four factors make the biggest difference.

On that last row, Prescient can incorporate a test result into its MMM as a prior. It shows you how the model performs with and without the test, and you make the final call.

What better search measurement changes for the business

Measuring search by the role each campaign plays changes where your search budget goes and which campaigns get credit for growth. That shows up in three ways.

• Credit for the campaigns that create searches. YouTube, CTV, Demand Gen, and non-branded search get credit for the branded searches they drive, so they're less likely to be cut.
• A clearer view of branded search spending. Saturation curves show where more branded search spend stops adding much, which helps you decide how much to keep spending on your own brand terms.
• A better-balanced budget. Money that isn't doing much on saturated brand terms can move to non-branded and upper-funnel campaigns with room to grow.

Where Prescient comes in

Prescient's MMM measures search at the campaign level for omnichannel brands, alongside every other channel and every place you sell, including your site, Amazon, and retail partners. It reports Modeled ROAS by campaign, measures halo effects into branded search and beyond, and updates daily.

From there, Media Forecaster shows what's likely to happen when you scale a campaign's spend or shift budget from branded search into other channels, so you can test a rebalance before you commit to it. If you'd like to see what your search spend is really doing, book a demo.

FAQs

Can a marketing mix model separate branded and non-branded search?

Yes. A marketing mix model can measure branded and non-branded search separately when they run as separate campaigns. The accuracy depends on whether the model knows they play different roles. Models that treat every channel as independent tend to over-credit branded search, because its spend rises at the same time as demand created elsewhere.

Why does branded search show such high ROAS in Google Ads?

Branded search shows high ROAS because people searching your brand name already know about you and are likely to buy. Google Ads and last-click attribution give that final search full credit for the sale, even when another campaign created the interest that led to it.

Is branded search incremental?

Partly, and it varies by brand. Some branded clicks come from people who would have found you anyway through an organic listing, while others protect sales you'd otherwise lose, for example to competitors bidding on your name. An MMM that models branded search as a way to capture existing demand gives you a more realistic read than platform reporting.

Should I stop bidding on my brand name?

Not without evidence. Turning off branded search can cost sales if competitors are bidding on your name or if your organic listing isn't strong. Looking at how sales changed during past drops in branded spend, alongside an MMM's read, gives you a much safer basis for the decision.

How do upper-funnel campaigns affect branded search?

Upper-funnel campaigns such as YouTube, CTV, and social introduce people to your brand, and some of them search for it by name days or weeks later. An MMM that measures halo effects can credit those campaigns for the branded searches and sales they lead to.