MMP in 2030: marketing measurement from the future
What does an MMP look like in the year 2030?
Well to start, no-one knows what “MMP” stands for anymore.
We’re in a time of massive change in mobile, in marketing, and specifically in the niche of marketing that is specific to mobile user acquisition. It’s an odd niche: there was no website user acquisition in the early days of Geocities and Friendster and Homestar Runner. But it’s an important and lucrative niche because mobile was the first truly personal computing platform. Built on the three-foot device (never more than three feet from your body) mobile offers unique access and intimacy to customers (users), making a mobile app install more valuable than a newsletter subscription, a website visit, or any of the other precursor actions to monetizing attention, service, or product in other customer acquisition modes.
MMPs were built to optimize growth in that niche, but the world is changing. What does the mobile measurement platform of the future look like?
MMPs beyond mobile
This is no shock.
Any MMP worth its salt is, if not omnichannel, at least multi-channel, with extensive technology to measure and optimize web-based journeys, old-school TV, connected/smart/OTT/streaming TV, email, and multiple other digital and non-digital channels. Sometimes that verges on simplistic — put a Singular link on a billboard, and boom! you’ve got a checkmark in the out-of-door category — and sometimes that’s sophisticated: correlating connected TV ad campaign impacts with app installs and/or marketing conversions via intricate data science.
But it goes beyond the obvious.
With the hundreds of billions of dollars being invested today by Apple, Meta, Google, Microsoft, and thousands of other companies globally to invent the next major computing platform, getting a “user” or (better yet) a customer won’t mean someone installing an app on a slab of glass and metal that slides into their back pocket.
At least, that’s not all it’ll mean.
Because “MMPs” aren’t first and foremost mobile measurement platforms, they’re first and foremost measurement platforms. The “mobile” part of the name is a modifier, and it could easily be replaced by smartglasses or wearables or even some futuristic cloud-based edge-capable personal AI that inhabits all of our devices and, like Tony Stark’s super-awesome but completely unrealistic Jarvis, has all the required data, access, answers, and insights we need at any given moment.
A world beyond mobile
Not shockingly, the world is not standing still.
For my Forbes columns and TechFirst podcast, I’m tracking at least 11 megatrends from smart matter to infowars to greentech and automation. Several are most relevant for apps, publishers, brands, and marketers, including:
- Artificial intelligence
I’ll go into more detail on these in a subsequent post, but suffice it to say that technological, social, and political changes are impacting the landscape in huge ways. Privacy will continue to grow. We’ll move farther towards a Ready Player One-style metaverse, continuing on the path we’ve walked since ARPANET more than 50 years ago and the first dim stirrings of HTTP in 1990. The yin and yang of centralization-decentralization will continue its pendulum swing, now trending (at minimum in terms of hype) in the direction of decentralization. And AI will infuse literally everything, becoming a core foundational piece of apps, software, and services.
With that as context, here’s a few things that you can expect in an MMP of the future.
Don’t take the 2030 date too seriously. Many of these exist today in some form. Many more are coming much sooner, but will be much more fully developed. And if I miss something you think should be on the list … let me know!
M is for multiple, many, and multitudinous
It’s obvious today but it will be increasingly necessary: marketing measurement platforms increasingly need to ingest data from a huge number of data sources. That doesn’t just mean many platforms and thousands of ad networks like Google, Facebook, ironSource, and Applovin. It means dozens if not hundreds of fundamentally different kinds of sources, often using vastly different methodologies, and combining it all to create data-driven insight.
Today, that looks like this:
- IDFA (in very limited supply)
Some apps still generate a significant percentage of opt-ins, which can still be useful depending on the other party in the adtech ecosystem getting opt-in as well. But I’d be shocked if IDFAs were still available in eight years.
At least until 2024. After that … see #4 …
- SKAdNetwork, or SKAN
Apple will probably be on SKAN v5 or v6, but the broad strokes will likely be the same: no granular data, privacy-first, minimal marketing data.
- Privacy Sandbox on Android (and web!)
Privacy Sandbox will be mature and full-featured and very usable, while still keeping granular device-level data behind a privacy shield.
- Cost & campaign data from ad partners
Wherever brands are investing in properties and buying ads, cost and campaign data will be available, providing both network-reported inputs (views/impressions) and network-reported results (clicks/actions).
- In-app data
Think of “app” broadly here … while it might be in some kind of mobile device like a smartphone, it could be an app on a pair of smartglasses or it could be embedded in another kind of device. The data will still be first-party data via logging, a CRM/DevOps/LiveOps type of tool, and marketing measurement or attribution SDKs or APIs, but each platform will have slightly different rules on what data brands can access or export, even if it’s on a first-party basis.
- Store data
App Store, Google Play, alternative app stores, and app stores on emerging platforms like VR and AR: all will generate somewhat analogous datasets around installs, ads, CTR, and A/B tests.
- Alternative economy data
Of course most MMPs ingest data about in-app purchases and ad monetization inside apps, but increasingly we’re seeing the rise of complex economies using platform or brand stores of value or cryptocurrencies. Increasingly we’ll also see these start to bridge apps and platforms, and they’ll be a more and more important measure of the health and growth of an ecosystem that publishers want to measure. Think blockchain-query-requiring insights like activity, value, recency, frequency, engagement, and so on.
Tomorrow, who knows what that will all include. Some parts are obvious, but some we won’t even really be thinking about today. Some options:
- World data
Weather? Sure. Climate trends? Macro-economic trends? Micro or geo-specific trends? Sure. Hype and buzz from all different areas of communities and verticals that drive people’s time and purchase behavior, both specific to a brand, specific to a vertical, and general but applicable to your business? Absolutely. Some of this happens today, particularly in massive and slow old-school incrementality measurement methodology, but it’s all going to get much more sophisticated.
- Cloud gaming
Well, it’s happening today, and is likely to continue to grow …
- Emerging platforms
Car operating systems, home operating systems, edge device data …
- Additional sources
We don’t know about them yet … but guaranteed there will be more than matter.
- Apps on Starlink?
- Mesh protocol services?
- Darknet products to cross splinternets?
Over the next six years, these sources will have to be broadened to multiple app stores (even on iOS) and multiple platforms both handheld, wearable, desk-bound, audible, home-focused, car-focused, and more … plus all the ad networks and marketing tools that grow up around each of them.
And, as I’ll chat more below, they’ll all add up to increasingly useful incrementality measurement in an age of aggregation not granularity, data but not trackability. Call it science, call it art, call it magic, incrementality is getting better and better and will be a source of not-quite-real-time insight for both strategic and tactical use.
Connected … built in to all your tools
MMPs like Singular already tie into major publishers’ data architecture via API or ETL, but BI is ridiculously bespoke today. Every publisher has something just a little different (or a lot different) which takes time, energy, and focus to build and maintain, and privileges the large and wealthy.
Expect this to get easier and quicker in the future, where the data you need for custom purposes is instantly connected/integrated/used in any tools you wish. Including, if you wish, your ad partners’ platforms.
Always-on continual incrementality testing
As mentioned above, this will become standard. Sure, this is in some sense already doable today, but it’s still fairly clunky and of debatable value: more strategic than tactical. It will become much more integrated into default, automatic marketing platforms.
Aligning the marketing campaigns you want to run against the measurement outputs you want to have — including always-on continual incrementality testing — should be automated right from campaign inception to close, with near-real-time reporting on how incremental each channel and effort actually is. And, of course, marketers should be getting suggestions (and perhaps also automated changes, see below) on adjusting spend and channel mix to minimize duplication or overlap, and maximize results at a given level of ad spend.
Modeled single source of truth
We’re operating in an increasingly uncertain world of performance marketing.
With the death of granularity, privacy thresholds, censored data, and missing campaign information already on iOS and coming soon to a theater near you on Android, few things are certain. (Although, let’s be honest, in the IDFA/GAID last-click era, certainty came with the cost of some amount of correctness: the world and a customer journey is much more complex than one click and one conversion.)
Multi-touch attribution as a function of near-total tracking is dead. Modeled attribution that intelligently mixes deterministic but aggregated platform data with first-party usage data with marketing inputs data will give marketers a model of reality that they can trust.
Within certain parameters. Plus or minus a certain percentage.
Some things are certain: when you act, there are impacts. Modeling those in an increasingly complex world of marketing data will provide a single source of — if not truth — or at least reasonably trustworthy truthiness.
And that will serve as a firm-enough foundation for future action.
There’s a significant amount of artificial intelligence built into a modern MMP, and it’s continuing to grow fast. Particularly in areas where you need modeled measurement due to censored data, or predictive analytics.
But the MMP of the future requires much less effort and knowledge to set up, and much less challenge to get what it knows out. Natural language queries? Sure, we’re seeing them already and they will be commonplace. Conversations with your measurement partner? Absolutely. Anticipating your needs and providing you the data you want when you want it, in the format you like it? Sure. Ad fraud warning signals? You bet.
Automated alerts are here already, mostly for known knowns and known unknowns. What about the most dangerous class of events, unknown unknowns? Brand danger due to a completely unrelated news incident in which someone wearing a t-shirt with your logo did something unspeakable in what is now a viral VR video?
You get the picture.
But that’s just the beginning. Today we’re already using machine learning to drive modeled insights. Tomorrow the inputs will be much more complex and the models much more refined.
Marketers can automate a lot today, including spend. There’s a lot more to come, including goals, recommended campaigns, suggested spend, plus automated shifts as the platform detects opportunities or weakness. Also, think AI-built creative changing automatically with AI-driven intelligence as your measurement platform senses failure. Tailored, of course, not just by platform or channel but across the board as winners and losers become clear.
Much of this is doable today in part.
It’ll all get significantly easier.
OK, sure, this is a bit tongue-in-cheek. But let’s be honest: ad networks like to own their own measurement (why could that be?) and suites continue to grow. The independent measurement platform that is solely focused on best-in-class marketing insights is in some sense an endangered species.
However, there are still some independent players with a hard focus on marketing intelligence for their customers. To continue to grow — and exist — they increasingly need to play well with others, so privacy-safe data can continue to flow.
Marketing measurement’s role: make it all make sense
For an MMP of the future, nothing changes in the ultimate mission. Which is, of course, to make it all make sense. What is the correlation between everything I’m doing to everything I’m getting … and which parts of what I’m doing are driving the best parts of what I’m getting.
When marketers know that, they have power. Power, quite literally, to change the future in ways that boost their brands’ growth.
That’s the MMP — if the acronym still exists — for 2030.