Occasional prospect: ‘What type of audience segmentation will you do?’
Us: ‘None.’
Meta advocates this approach today, and almost all of the time, it’s the right path to follow.
I had a conversation with friends who don’t work in marketing about what targeting on Meta was. There was an assumption that as an advertiser, we had access to all that data that is used to target ads at you.
“We’re going through a once-in-a-generational shift of how businesses grow”
From the more cynical (‘I had a conversation, my phone overhead, then I got an ad’) through to the more standard (‘you must know because I’m a 34 year old woman, you can send mother and baby related content to me’), there is a great unknown about what actually goes on in Meta’s black box.
I’ve been reflecting recently on what some of the big fundamental marketing shifts are at the moment. As I’ve written before, I believe we’re going through a once-in-a-generational shift of how businesses grow1.
One of those big changes is how we think about targeting.
This is interesting because our collective understanding of targeting has shifted a lot over the last few years.
The result of that change is that today, we run 99% of our consumer accounts in totally broad mode. We exclude as little as possible. And we aim to target both new and existing customers.
There are people out there who still disagree with this. Doing the opposite makes you look active and busy. But today, it’s redundant behaviour.
The conflict between marketing that works for the biggest brands and startups
There have long been conflicts in the startup marketing world of how you should think about targeting.
Les Binet in his seminal Long and the Short Of It, reinforces the important of being your advertising being ‘broad’ – by which he means including potential customers who don’t yet know about you, as well as the existing ones.
Meanwhile, you’ve got now 30+ year old books like Crossing the Chasm talking about the ways you have to shift gear so that you can move beyond early adopters and into the mainstream.
And then you’ve got texts like How Brands Grow, which talk about the importance of building long term mental availability.
None of these feel controversial until you consider the parameters that startups operate in. A reminder that startups are not just new and small companies. Startups are by definition designed to grow big and fast. A new barbershop is not a startup, but a marketplace for haircare may well be.
The startup funding environment reinforces this. It requires the belief that you can reach $100m/year in revenue. The best way of demonstrating that is by showing continual, fast growth.
And so the canonical view of how to grow big is at odds in many ways with realities of growing a startup. Why?
Because if you focus on a less broad approach, it’s often cheaper so you can acquire more.
Because educating the market is expensive, and so it’s better to focus on customers who have a higher problem state and are willing to pay for shoddier products.
And because you need the customers who convert inside this month’s P&L so you can report it back to investors and build momentum for that Series A.
As a head of growth, or indeed a founder, you live and breathe by your growth rate. All of the academic, best practice teachings that exist in many books, just didn’t apply in reality. We’ll focus on those later down the line.
Targeting on the Good Old Days™ Facebook Ads
The old days were far more the job of a media buyer, than a creative strategist. Targeting was the key. I remember getting access to loyalty card data that showed supplements buying habits. That’s really powerful to be able to know that, especially when combined with all the other cross-sections of how we divvied up that data and controlled each penny and pound.
It lulled us in to a false sense of control.
And it reinforced this view we had that the long term view wasn’t the right one. That tiny, niche audiences were the best way to go.
Since iOS14.5, that has all gone away. And thank God.
Media buying today is broad, targeting is creative
We run almost all of our consumer ad accounts super broad. Why?
First and foremost, I’ve got no belief or frankly arrogance that I can outperform Meta’s machine learning. For a decade, Meta has been able to outperform a spouse in predicting user behaviour, why would I believe I can find people better than it can. It simply works better to be broad.
Second, and more importantly, because it means that creative can finally be the targeting.
This principle always existed. Inside your lookalike stack, Meta was doing what it could to find the right people. But it was within pre-determined confines that advertisers set.
Anyone who has ever run a Jobs to be Done interview process will know that you can find people who are demographically opposite, and yet both fulfil the exact same buying reason. Targeting those people on Meta should be done with the same strategic approach.
Targeting with creative is not zero sum. There is no ‘best ad’, there are ads that acquire certain types of people, and other ads that acquire other kinds of people. Your CPA is your stop-loss signal.
I know this feels scary to many. Especially when you know that most of your customers are female 35-44 for example. Why not just narrow down targeting on those? (And definitely avoid ASC!).
We by comparison run ASC on a series of products where they are designed for a specific birth-assigned sex. Traditional advice would imply we should target those to female only or male only. ASC doesn’t do that, but the algorithm very quickly works it out.
Using processing fluency to target using creative
Targeting with creative comes down to one core cognitive bias: processing fluency.
This is the bias indicates that we act more favourably to things we can process faster, and we process things faster that are more familiar.
With that in mind, our creative should be designed to fall naturally into particular people’s existing frameworks. Creative becomes your targeting.
Here are a few key principles we always follow.
Use the simplest language possible
Complicated language is universally bad. It is it harder to understand than simple language, and takes longer to read. Plus, contrary to your intent, it often signals a lack of knowledge. As Churchill didn’t say, ‘it takes a long time to write a short speech, and a short amount of time to write a long one.’Jobs to be Done has far more scale than product features
Ads that talk about features do work. If you’re the type of person who compares prices on similar items, or builds a PC rather than buys a Mac, then you’ll respond very well to ads listing detailed features.
But there is a definite cap on those audience sizes. Using Jobs to be Done language and understanding is the the best combination of scale + efficiency we’ve found.
JTBD language needs to mirror the customers’ language. Every time we stick a direct customer quote describing their problem into the hook of an ad, there’s a strong chance it’ll work.
There is a wider group of people for whom JTBD will match their processing fluency.Mirror their cultural cues
If I wanted to advertise a product to the residents of north London’s Clapton right now, I’d mirror the visual cues of local meme account Real Housewives of Clapton. Those memes are so pervasive within that community, that they have accrued processing fluency within the audience.
Everyone has their culture. Their identity. Mirror those in your ads.Walk a mile in their feed
As discussed a few weeks ago, as advertisers we interrupt2. That means we need to embrace the environments we’re in. Don’t try and crowbar your own visual style in. No-one cares what your brand guidelines are. They want problems solved. They want produces they believe in. And companies that reflect who they are.
This is the new targeting. Be as broad as possible in your media buying, and as specific and mirroring as you can in your creative strategy.
We’re going through a once-in-a-generational shift of how companies grow, and this is central to that.
Bite of the week
Taylor Swift – Midnights album launch on social. A few months old this but I found it this week. Jellyfish’s Rhiannon Davies did a full case study takedown of Taylor’s Midnights launch on social. This is a great read and the sort of nerdy read I’m sure many of you will enjoy.
Bill Gurley wrote on X yesterday that VCs holding loads of cash doesn’t mean they are incentivised to burn through it and should provide caution to those that think it does