Forget personalisation, it’s impossible and it doesn’t work
marketingweek.com
marketingweek.com
Similarly, clothing brands like stitch-fix and trunk club are personalization specific.
Regarding Disney, we just signed up for Disney+ and the first step was to decide if you wanted mature content and the second was to decide on your avatar. I think Disney+ will allow the company to cater to personal tastes more than they ever could through theaters and we will see that in the future.
Finally, for the longest time marketers have looked at demographic groups to target with their products, this is a weaker form of personalization. Obviously that won’t be abandoned, so I wonder why the author thinks companies should only target mass markets?
You're talking about their recommendation engine for users they already have, which is completely different.
We also have to take into account that there's a lot of "misses" in those recommendation engines - which is normal. But when they nail it, people have positive emotions towards it, so it's a good feedback loop.
Personalization would be to have Spotify recommend you only songs about expensive watches after you've searched for a Rolex on Google, with ads in the middle about Rolex ahaha.
You mean the recommendation engine? Hardly ever it worked for me.
What Spotify is built on is "play albums/songs you select or follow playlists on genres you like". The recommendations are tacked on, and bad.
Maybe it varies dramatically by genre?
For example, take the "Phonk" genre, which I only was introduced to due to the Ukrainian war. To mean these recommendations give me a lot of new music to listen to. But then you have people lamenting that "Phonk" has really been overtaken by "Drift Phonk". https://www.youtube.com/watch?v=UAV7hnCB_ZE&ab_channel=yokai
On the other hand, I personally enjoy albums and songs major artist after they achieve critical success, when they establish their signature sound, like David Bowie(1970-1983), Stevie Wonder (1972-1976), or Peter Gabriel(1986-1992), but if I "like" any of these songs on Spotify, it means I get their entire catalog mixed in my daily mixes, and if they ever release a live album, those tracks show up. This is not what I want.
Music genres change, that's nothing new at all. Just look at the type of trance from the early 2000s and compare it to today's trance. It's a completely different sound. Would the author also complain about "progressive trance" taking over "trance"? It's natural that some sub genres might become more popular, while others lose listeners relative to the newcomers. Same happened in techno, rap etc.
While Spotify might accelerate this process through a positive feedback loop, this video is just another form of gatekeeping and saying "I knew XYZ before it was cool".
Which is neither here nor there. Apple music came later, and Spotify already had a headstart, a good UI, a good selection, and a good free plan.
Spotify, Pandora caught on because they were the first good streaming solutions, at the time bandwidth, mobile phones, etc, were in place and ripe for streaming. Not because of their recommendations...
I prefer to use YT Music s it seems thoroughly confused by having each person in family use from my service account to the point the suggestions are general in nature. They still do not get played though. I refuse to click on suggestions in any product as that reinforces their data on me/us. I’m quite ok if any music engine thinks I’m a polyglot toddler with penchant for death metal, Thai ballads, and ancient Chinese orchestral Music. Such a profile makes me soooo much less likely to get other music or junk marketed to me ;-)
Sure, I've had some good recommendations, but I'd expect any recommendation engine to do that just by chance.
What I can say is that Spotify has never proposed something truly new and interesting to me. If I listen to a lot of metal, it'll recommend me the most bland stuff in the same genre. What's even worse is that it keeps playing the same songs over and over again. It's like the recommendation engine just gives up and starts repeating its suggestions again.
I simply gave up on it. Why have access to everything when I only got the crap. Going back to my personal collection increased my good/bad song ratio considerably.
"It" being reality?
>If Spotify's recommendation engine wasn't as good as it was, it would not have the users it has
Now that's just confirmation bias + circular logic.
A streaming service can have users regardless of how good its recommendation engine is. YouTube has crappy recommendation (and has had worse for most of the time it existed) but tons of users.
For Pandora and Spotify, merely offering a convenient way to stream music, a free tier, and a big catalog, was enough.
You seem convinced of some bizarro idea that a media/streaming service can only succeed based on its recommendation engine.
Where did you get that from?
That's not an argument
Canceled and would not consider a recommendation based service that does not let me explicitly remove something from being recommended.
Disclaimer: I work for Spotify nowadays but have been an avid user for more than a decade before joining, my opinion is based on my personal experience with the service and not as an employee.
As I read this article, this meaning of "personalisation" is not the one used by the authors.
Tech companies like Spotify and Pandora are just intermediaries. They may help to "deliver" commercial product, or advertising, however they do not create the product referred to in this article. The article uses the term "personalised creative" to refer to product. Tech companies operate as middlemen and produce no content. They are dependent on others to produce it. This is the bait for computer users. Tech companies sell advertising services to companies that produce content.
Tech companies gather data about individual computer users, e.g., web browsing histories. This is "personal" data. Tech companies allege this makes it especially effective and therefore valuable. The studies cited in the article suggest this is claim is false.
Disney produces content. There is no shortage of personal data being collected and sold by tech companies which is available to Disney. The article highlights that, despite the availability of personal data collected by tech companies, Disney generally does not produce "personalised creative".
In sum, the article is not about what "tech" companies do, it is about what content producers do. More specifically, it is about whether, based on available research, producers of creative should or should not attempt to use personal data about computer users collected by third parties in order to produce "personalised creative".
They do create a "product", the delivery system. This is a creative product as much as any of the music. A lot of software was written to allow this and all of that is the "product".
Most major value creation happens well before Disney+ or Pandora. They just have somewhat broadly defined parameters that will get you more of the same, from what has been created.
As easy examples, there are a lot of good kids shows that adults could enjoy, but my guess is that they are not recommended to most adults. Just as really good folk music is likely to get suggested to someone that hasn't listened to folk music. Or music/movies from another nation.
Which is all too say that the personalization is ultimately a customer fitting themselves to what they want, from what they know. Dropping someone in fresh with no prefit is probably a lost cause. Even though that is how most personalisation talks brand themselves.
Just remember that when you think this, the reality is that you are just that predictable based on half a dozen meaningless datapoints.
In fact, they're actively building it and selling it to advertisers. Disney+ and similar platforms are the tools that media companies have every intention of using to drive the accuracy numbers much higher.
E: I should note that I work for Snowflake, we're marketing this capability pretty hard. I'm not directly involved though.
(Or so it seems to me)
I mean if you are into a movie there might be only three ones like it which you allready have watched and surely are not on Netflix.
However, as soon as you use your Spotify account for kids or parties the engine gets messed up forever. It is a shame since it helped me find alot of artists.
Any time Spotify is brought up (which is really any time music is brought up) it's a good bet the quality of discovery of recommendations are mentioned. The Discovery Weekly and Daily Mixes are loved. My anecdotal evidence is the dozens of people I've talked to about this over the years. This HN thread is the first time I've seen anyone suggest otherwise.
I know for myself, if it wasn't for the discovery that Spotify offers, I wouldn't use it.
I also prefer Spotify user-run playlists better, which I pick myself, searching for genres and songs explicitly.
Nothing to do with preferring the personalization.
"No" seems to suggest that you're disagreeing with your parent's post, but your parent is saying why they chose it, not why you did:
> I assume, perhaps incorrectly, that everyone has the same catalog (at least for my fairly boring taste in music) and actively choose Spotify’s personalization over Apple Music’s tighter integration with my phone, car, etc. Just a single data point though.
And I am saying why I chose it. You don't need to read too much into the "no", nor have to find some perfect formal consistency in a quick response. It's just "no" as in, "no, that's not my case".
Even if personalization worked, I wouldn't want it. Not just for the obvious privacy reasons, but because it would not be relevant to my current context most of the time. If I'm looking at a camera review page, I don't want ads for flower bulbs or shirts or whatever else I may be interested in. If there has to be ads, make them relevant to the context. I would be much more likely to buy some camera accessories from such a page than something irrelevant and distracting.
But yes it does help sell more. If they are keeping track of what people by to target advertising, I'm sure they are measuring the return. An expectant mother seeing car seats in a flyer from Target is going to be more likely to go look for a car seat there than someone who doesn't think about Target having a car seat and orders it off Amazon or else where simply because they didn't think to go look at the car seat section in the store.
In the context of this article, I would just like to see 3rd party cookie alternatives that do some of this better without tracking.
Most ads are for garbage I don't want/need, and many are scams, but there are still a number of ads out there for things that I would buy if only I knew they exists.
For the expert to be incentivized to give unbiased* advice, 100% of their income needs to be from the customer, and 0% from the car maker. Which Bluntly put, this boils down to making marketing departments illegal.
(Note that a car magazine with ads, where the experts' income depends on both readers' eyeballs and car makers' money, is still way, way better than relying on car ads.)
* 'unbribed' would be more accurate, as there would still be some biases to make the readers feel happy to follow their advice, e.g. favouring short-term satisfaction over long-term safety, etc.
Metrics that track good faith interactions are needed, like eBay reputation - if someone isn't 98% or higher, they're going to be overlooked or bypassed in favor of someone with a higher score.
Product reviews and ratings get gamed, because current systems don't reward good faith transactions - Amazon and Google customers purchase attention and shuffle facts around top maximize purchases. If quality reviews and curation were incentivized, there would be a thriving class of reviewers and experts playing a role in the marketplace. Their absence is glaring, and the horde of product influencers and professional reviewers underscore the deep corruption of adtech. Those people leech money from the market by selling the ability to lie. The lies are sanctioned by adtech firms, and often laundered through otherwise reliable data sources.
Any legitimate attempt to compete threatens the entire adtech ecosystem, so a majority of all consumer marketplaces are incentivized to cultivate the corruption and prevent any changes or reform that threaten the sanctified lies.
Things like Angie's List and product review vlogs and expert podcasts are stuck within the system, regardless of their intent or functionality when they start. They eventually converge into niches that support the system as a whole. Even reddit, requiring individual human dialog and interaction, has been infested by professional reviewers shilling crappy products.
You can't trust the data sources because trustworthy sources are incompatible with adtech. Google has sufficient data to fix it, but they'd lose money by allowing reform, so they maintain the ethically gray areas ferociously. Their business is not quality search, it's maximizing advertising profits, and it's more profitable to have 50 people paying a premium for scraps than 5 high quality vendors with vetted products earning those spots through quality and service.
The system is working as intended.
Why not put all ads into a website that is dedicated to ads, so that users who want them can look them up?
Please read the article again.
Unless you're maybe saying "the problem isn't the targeting, it's the type of ad"? But I don't see anything in the article that makes it specific to banners.
They are talking about ads, not about which songs are suggested to us.
> Most personalisation efforts are powered by third-party data. Marketers infer who customers are based on their browsing behavior.
In order to deliver personalised ads, they use cookies — third-party cookies, by companies that invade our privacy and track our every move.
Spotify does not rely exclusively on poor quality third-party data: they also have first-party data about us: the songs we listen to, like etc; how often we listen to them; if we put them in our playlists etc. This is one reason why their guesses as to what we may like are better.
Another reason is that they are ‘only’ trying to suggest another song to a person who, apparently, likes music; they are not trying to guess my gender, age, job, wealth, type of person I am, mood, interests etc and find a match between these tracts and the fact that I may be interested in… an ad I never requested from a company I don’t know…
> “We determined there was simply too much waste in the old model of activating this third-party cookie-based data across high-reach, low-impact placements.
My guess is that the type of ads they are talking about here are general rotation banner ads, i.e. garbage worth nothing which gets sold for good money under the (false) promise that companies have ways to show your ads to the ‘right’ people. Problem is, they don’t.
It has a big list of media and it's trying to pick one that will be effective on you. That part is quite similar.
> Spotify dies not rely exclusively on poor quality third-party data: they also have first-party data about us
Is that why they're saying it doesn't work? Or is it a different reason? Because I see people citing all sorts of possible reasons and intuition can only go so far in knowing which ones are important.
> My guess is that the type of ads they are talking about here are general rotation banner ads
Maybe. But in that case how much is the data the problem and how much is the type of ad the problem?
The problem is the type of ad, which is worth nothing. The data is just BS used in order to dress up the selling of a worthless ad placement for good money; and yes, that data is also largely flawed.
And even if it were not flawed, ‘guessing’ that someone who is supposed to be a certain age, gender, in a certain job, in a certain relationship, with or without kids, etc could be interested in a certain product is much harder than simply guessing that if you like these 10 or 100 songs, you may like this other song.
And how is anybody going to ‘prove’ that all this quasi-magical targeting worked, when click rates are ridiculously low even for highly targeted ads?
Imho targeting and ‘personalisation’ serve just one simple purpose: convince the marketer that he/she is doing the right thing, or what is considered right or best practice at the moment, and so that they are safe and are not going to be fired because, you know, nobody ever got fired for choosing IBM.
The Spotify data about like/dislike is rather accurate (like 80-100%), as long as someone doesn't click under substance influence.
Third party data (according to article) has accuracy around 4%-44%.
Ads deal with real life, does your AI engine know that because of a deadly heatwave sales will change?
Guessing which songs I may like based on 10 or 100 songs I like, while not trivial, is possible.
Guessing who I am and if I am the right target for a kind of ad (broad-reach, low-impacts ads) nobody pays any attention to anyway is delusional.
Pull the straw-man apart a little bit: 3rd-party data isn't the only data out there. There's at least one solutions (full-disclosure: I'm building it) that uses high-frequency communication channels like push notifications as a factory to originate 1st-party data that's tailored to your business needs and exists at the individual level. In other words, saying personalization based on 3rd-party data doesn't work is like saying a car that with water in the gas tank doesn't work. Of course it doesn't. Stop putting water in the gas tank.
Now look closer at the analogy: like a good movie, a good marketing strategy will expose customers to a wide variety of reasons to engage, so they can take what is personally meaningful to them and leave the rest. You can't fit the whole strategy into a single message. Of course you can't, just as Disney/Pixar can't fit every emotional association into a single scene scene. The authors point out the obvious fact that personalization can't fully happen at any single point in time, and miss the point that personalization necessarily happens progressively over multiple points in time.
I don't mean to come down hard on the authors of this post. They're reacting to what most marketing platforms call personalization. The problem isn't that personalization is impossible and doesn't work. The problem is that so many platforms have implemented something that doesn't work and have called it personalization.
For anyone interested, my co-founders and I have written several blog posts covering both what real personalization should look like, and many of the technical aspects of how it can be both possible and effective: www.aampe.com/blog
That is, the dream that a bike company can use personalization to get better market penetration with their emails is dubious. Even a category store can only tailor their message so much. Is why most bookstores all have the same books.
This goes as far as medicine. People want to think that a personalized prescription would be far more unique for individuals than the truth of it just being slightly tweaked.
Just think about timing: when is the best time for someone to get a message from you? There are aggregate stats about certain days or time being better for open rates, but customers aren't a monolithic entity. Some times work for some customers, and other times work for others. We've found that timing decisions have huge impact on ROI in industries ranging from gaming to retail to food delivery.
Now look at topic: what kind of bike do you try to interest them in? Do you try to interest them in a bike at all, or do you pitch a helmet, or shorts, or repair services. Personalizing topic is the essence of a recommender system, which has been discussed elsewhere in this thread, and it's possible to get something like that, even for a bike shop.
Then you have text: let's just look at value proposition. Do you appeal to their love of the open road? Their desire to exercise and get more fit? Spend time with their families? Replace an old bike that's causing them maintenance headaches? By learning what aspect of biking individual people care about, you can tailor subsequent communication to emphasize those things.
A bike company has virtually endless ways to tailor their message.
And, as is usual in product companies, getting price under control will almost certainly have more of an impact on sales. That and just getting in front of more people, period.
> Personalisation assumes that marketers have perfect data on every individual customer.
No individual believes this, so it's hard to believe an extrapolation into organizational commitment.
> Marketers infer who customers are based on their browsing behavior.
Not in isolation. This is mischaracterization.
> So, how accurate is gender targeting? It’s accurate 42.3% of the time.
Probably not. There is no access to the datasets (https://pubsonline.informs.org/doi/epdf/10.1287/mksc.2019.11...). "Gender accuracy ranges from25.7% to 62.7% with an overall average of 42.3%" without explaining how "no data" is handled. Having the actual data 42% of the time and not having it 58% of the time isn't the same as measuring how accurate it is. This looks like using bad statistics paired with confirmation bias.
On and on and on.
This is an article built on a quick summary of a questionable paper to push some anti-marketing prattle. Not to say that DSPs are reliable or that everyone is handling legitimate data, but bad data is filtered out pretty quickly in AdTech where there are means-tested costs...although it sometimes takes time to present.
One of the most interesting usecases of my company (videobolt.net) is personalized videos at scale (via API or one time video creation on a bunch of data). We powered some very interesting campaigns this way.
This perfectly demonstrates the point of this article - it's a canned and mass-produced product.
As far as I understand the article, two main points are that data on which you think you're doing personalization is often inaccurate, and that even if it is accurate you cannot hit the person well enough because that data is not enough.
As said, I pretty much agree on acquisition level, but don't on retention level.
On retention level, data should be good, since you are the one that is collection the data through your app / service usage. You should collect important data and trust your data.
If you are sure you have that data, you may very much provide your customer with interesting personalized marketing experience.
For given example, people use that platform every day, enjoy it, and are proud of their achievements there. They very much liked and shared these videos, as they are telling story of their journey on a platform that is important for them.
PS. I agree this is not for everyone. You should have immersive platform users are spending a lot of time at, with a bunch of interesting data. These would maybe even work on remarketing level, if you collected enough data in your system for given customer.
PPS. And difference between good quality video and PPT / GIF is... just huge.
(I’ve worked for one of the top TV and cinema content companies in the world, and currently working for one of the top DSPs (advertising)).
There was a post a little while back arguing that Avengers isn’t even a kids franchise anyway, so your observation still stands.
> In an academic study from MIT and Melbourne Business School, researchers decided to test the accuracy of third-party marketing data. So, how accurate is gender targeting? It’s accurate 42.3% of the time.
If this statement is correct, does it mean that gender targeting is worse-than-chance? I am willing to believe that the data is poor, but find it had to believe that it is THAT poor. Am I misunderstanding something?
What percentage would all the categories that are not male and not female need to be in order for 42.3% to be better-than-chance?
> The other genders are faddish nonsense.
Gender is a touchy subject. While there is a lot of room for disagreement, it is hard to deny that some people are born in a way that does not fall neatly into the traditional male and female categories. It's dismissive to talk about it as faddish nonsense. It does not help people to understand the world around us better. Instead, it reinforces simplistic thinking about a complicated world.
https://medlineplus.gov/ency/article/001669.htm#:~:text=Inte....
One is a biological condition of sex development, the other is a social issue, largely caused by the idea that there are certain thoughts and behaviours that are inherently masculine or feminine.
So for example, if you're a woman who doesn't "feel like a woman" (actually: at odds with cultural stereotypes of women) you might choose to identify as non-binary. Which is happening a lot more these days, amongst some populations - so I think this could reasonably be called a fad.
> Recently, Professor Nico Neumann partnered with the brilliant marketing team at HP to replicate this research for B2B. The results were unsurprising – but horrifying. Many enterprise technology companies spend millions of dollars ‘hyper-targeting’ IT decision makers (ITDMs) using third-party data. But if we get gender wrong more often than 50% of the time, what percentage of ITDMs do you think are actually ITDMs, according to the research?
> Do you want to guess? It’s 14.3%. And for ‘senior ITDMs’, that number drops to 7.5%.
> Super impressive! That’s about as precise as… a drunk monkey throwing darts?
That... seems... like a great result? How many ITDMs are there in a random sample of 10,000 people? According to the Bureau of Labor Statistics [0], there are 715,000 people working as IT managers in the USA. So the incidence in a random population of 10,000 is 715,000/300,000,000 = 24 people. Seems like the ads are working really well.
I think it's interesting to see when you get a targeted ad you benefit from. I attended HackMIT for the first time after seeing a Facebook ad for it--I had an amazing experience at the event and that ad is possibly the reason I am a software engineer today. I doubt I would have received that ad if targeting weren't possible.
If I had to put my imagination to work where ads and humans can coexist peacefully, I could imagine a world where ads are required to be hyper targeted, and you would be shown no ads unless the ad was specifically targeted to you. If the ad wasn't relevant to you, you could click an x on it to make it disappear, and the advertiser would have to pay a penalty to the host of the ad (google, facebook, whatever) for inconveniencing their users. I suppose marketers at Disney and P&G would suffer, but I am really sick of seeing liberty mutual ads when I don't even have a car.
The article is arguing that instead, you should just craft a "Buy Viagra for you or your spouse because of these broad based benefits of Viagra" ad that is for everyone.
Which in this case would be something like putting ads up on a website or magazine that’s know to target an older male demographic. Or getting an older men’s health influencer on Instagram/TikTok to make a sponsored post. So still directed marketing, just not personalize on a user by user basis based on data from 3rd party brokers.
Hyper-individualized ads are just plain creepy. I’m glad to hear they’re generally ineffective at reaching their intended audience, and I’d hope that when they are effective, that the sense of invasion people feel causes them to turn the other way.
That's the Victoria's Secret business model, or was, so it's not necessarily a bad idea.
Similarly, I've used the same tax preparer for the last 10 years, and never, ever, ever have I had a refund. Every year, I get the emails about "your refund is waiting for you". I get that the marketing is outsourced, but it's so annoying that the one thing I'd expect tax company to know about me isn't used.
Their data somehow resulted in a statistically significant anti-correlation. This is a pretty unlikely result from a stats POV.
This is a lot more plausible than you might think. Simply build a machine-learning model that is accurate 58% of the time (maybe because it takes the "gender" field people manually entered on their online profiles and adds noise) and accidentally invert its output.
> Can you name a single brand built on personalization ?
What does this even mean. Brands which rely on personalization on a product-by-product basis ? This seems only possible at scale for digital products. Tik tok comes to mind. How can a brand rely on personalization ? Either the product is tailor-made or it isn't. It's not like the McDonald's logo looks different to different people.
Are there good studies on this to validate it?
Companies spend a mint on this stuff because they are told it works and is necessary, I'm not sure that's true, especially when that comes from the sales/marketing arm of those ad companies...
Now if you need to target 100k hyper specific audiences, then it's a different story.
Let’s forget the obvious demographics correlation with products and just start with an example.
Simply knowing that someone is active on HN, I wills bet ads on tech product and services would be more effective on them compared to a random person on the internet. The problem comes when the personalization gets too personal and stuck in the past, like how Amazon recommends another of the same product category after you bought one.
Also, exactly half of this website is taken by popup "Subscriiibeee!!" pane without close button. What a waste of time.
And meanwhile, can we also junk all those massive steaming piles of cruft code attempting to personalize web & app experience? What an enormous waste of every user's time, and many coders' creativity. Ugh
Over the decades, I've seen a literal handful (as in <5) adverts that worked for me extremely well - brought me relevant news of something that I didn't know about and was useful, and sometimes even lead to a purchase. Those were ALL clearly based on the context of what I'd been reading, and not some "personalization". The other 99.99999% of the adverts I've seen browsing in the past 25+ years is utter trash.
Remember that old saw about "half of all marketing dollars are wasted, but no one can tell what half"? Wrong number - it's 99.99999% wasted.
This author is clearly engaging in hyperbole to gain attention and drive new clients. Zig when others zag.
Literally no such thing.
If you're actually involved in creative work, knowing your niche is extremely important.
None of that were ever true (well, unless you accept the simplest explanation for that anecdote that the daughter accidentally Googled something related), this is definitely not true as of today.
> Disney only invests in creative that works across all segments – angsty superheroes, lost animals, magical princesses.
Are these quotes typos, or is "creative" as a noun some sort of jargon? I find it really grating; what was wrong with "media?"
>I find it really grating; what was wrong with "media?"
We use "media/medium" to address the distribution channels of the creatives.
"Content" is used more for long form/non advertorial type of content, like blog posts, video expanding on a subject, etc.
> As a non-native speaker, it was really grating and hard to read, but obviously you're not supposed to understand other industry's jargon.
Yes these are industry terms, for example: the term "copy" is also a very old term used to address the "written" part of ads (of course is more than this).
In the end it's all content and media, but it would be very hard to specify what type of content and media using these broad terms in this context.
I think different versions of the same movie would completely break word of mouth, though.
Story branch decisions in gaming are to some extent just an evaluation of what the writer's think of your world view - at least when it comes to consequences. Arguably they can only really be constructed as a trial between two opposing narrative voices - resolve questions of character via the wisdom of the crowd.
Discussion and memes based on movies don't work quite well if everybody is watching a different movie.
Similarly for a movie, perhaps we could personalize them, but would the result actually be desirable.
I'm so surprised that there are memes from big hits, but no real talk about them.
I mean there's relatively a lot of talk about how Harry Potter feels good but doesn't make sense, and of course lots of critiques, reviews, "reaction videos", but somehow it seems actual people stopped talking about movies with each other (beyond the very shallow have you seen it? yes/no. was it good? yes/no.)
maybe I just miss when people talked too much about the Matrix? :D
also I find it strange that it's still so hard to find good movies/books/series/games that I would like.... despite all the data, metadata, taxonomy, folksonomy (tags! unstructured data! big data! bad data, bad!)
for example, IMDB knows what I like, Netflix too, yet the recommendations are pretty bad.
let's take Mindhunter. "CSI done well", right? but I still haven't found something that is similar to it. (not that I looked very much.)
And to run counter to this article - people have been going after niches for centuries. To great success.
Without going super deep into the specifics they do make one good point that I agree with which is using 3rd party data brokers and sources to drive a personalisation strategy is going to give you terrible results precisely because that data is junk to begin with and is probably only going to get worse over time.
That is however probably where the good points in that article end.
In short, they take this ultra narrow view of what personalisation actually is and just straw man it to death.
There is an underlying principle in the world of sales / marketing etc that basically boils down to show the right people the right message at the right time. The idea that this approach doesn’t work is not in anyway backed up by any evidence whatsoever and the second half of the article that just says “make something great for everyone because… movies” is just incredibly stupid advice.
Like yes that is a great baseline to start from and is a goal in and of itself but what about when I start to know a bit more about what you’re actually looking for? Why would I not intentionally try to tweak my approach? A human salesperson who couldn’t adapt their approach would be out of a job within a short amount of time.
The problem ultimately comes down to how can I understand
1. Who is the RIGHT audience
2. What is the RIGHT message for that audience
3. What is the RIGHT time to show that message?
So it might come as no surprise to anyone that if you just outsourced that question to some 3rd party data source and had some incredibly broad and useless audience group like “women 18-24” then your results are going to suck for a multitude of reasons.
Just for the sake of contrast let me demonstrate a simple but otherwise realistic example about how you may want to think about personalisation using a topic you’re all familiar with.
Let’s say you’re working for GoDaddy and you’re trying to improve the revenue of users who land on your homepage for example.
You are going to run a lot of A/B tests to figure out that first part I mentioned before regarding what’s the best possible version of this page I can show to people in general and tweak all kinds of things like the kinds of products / offers I push (domains vs hosting for example), the order I show them in, the way I talk about them etc.
Cool? Concurrently to that I’m also going to start thinking about what are the kinds of customers we have.
For example, GoDaddy have a pretty wide variety of customers when it comes to technical sophistication to just pick a random audience attribute that is actually relevant.
There are a lot of HN crowd types who just want a cheap domain but want absolutely nothing to do with GoDaddy’s otherwise not great hosting plans. There are people who want very specific kinds of hosting like Wordpress, there are lots of non technical small business owners who are just trying to get setup with something basic and aren’t sure where to start among many other groups.
So I’m going to start thinking about where could I find those specific groups of people both at a targeting level (ads, sponsorships etc) and also from an identification level (I.e. maybe the referrer string on the HTTP header shows HN for example, maybe I see they are coming in via one of the ad campaigns I set up earlier specifically targeting Wordpress hosting, maybe the user agent shows a windows vista user running IE which says maybe they aren’t likely to be technically savvy etc)
Now I have some additional contextual information that I can use when I need to make a decision about what offers do I want to show in the hero section of the homepage for example. Do I push domains? Do I push how we specialise in working with non technical users etc.
That kind of thing works, consistently. That’s the right message to the right audience and at the right time (to be fair I’ve not really done anything with the time angle in this example and am just assuming this is the first time they are interacting with our brand) concept in action. You can make things way more sophisticated obviously but that idea alone at GoDaddy scale would make meaningful amounts in additional revenue, no question. That is something very different to what the narrow example they used in the article however.
That's kind of the industry mantra for us, marketers. The reality is much more complex than that, goes beyond that to be quite honest.
You just have to ask the question: "What's the right time to reach the right someone, with the right message?"
And you'll find out the answer to that exercise is a game of Darts, with hits and misses, and as a consequence a lot of wastage. But that's the game we chose to play.
Now, of course if you're reaching people who left your eCommerce shop and you retarget them with the items they have on their basket, it's a personalized ad that has a great probability to get results because you are reaching people who expressed a very specific behavior. But this, as you know, it's a rather small slice of your potential customers.
But for example, when you say:
>useless audience group like “women 18-24” then your results are going to suck for a multitude of reasons.
If your product offer is a pill that helps to relief period pain and cramps, why isn't this a valid audience? Or the pill needs to be a "a pill for early teen women that like skateboards and scratch off tickets"?
In my point of view the problem isn't the lack of personalization, or the need for it, but more a matter of saturation of some media channels.
As for the straight up demographics example I called out I think that would work ok in theory but suffers from the major problem that you can not accurately identify that audience group to begin with and often doing so gets into the sleezier side of marketing that I personally want nothing to do with if I can avoid it.
On top of that, I think there are better approaches, women 18-24 are not one homogeneous group with the same wants and needs and treating them that way might work better than the idea of let’s just show the same message to everyone all the time but I hardly think it’s the pinnacle of tailoring your content either.
Personalised ads result in vast amounts of corporate surveillance and still don’t work. I’ve never understood why contextual ads aren’t seen as good enough. If I’m looking at reviews for baby products, for example, then probably going to be interested in ads for similar baby products.
And with personalised content or product recommendations, very few companies have the breadth and depth of content that even begin to make it worthwhile, and even those that do can’t seem to do more than show you more of what you’ve encountered before. YouTube and Instagram’s personalisation algos can be downright annoying ‘You watched that one video randomly? Okay, here’s hundreds more like it, crowding out all the things you do watch regularly.’
Good search and discovery tools are always better than a stupid recommendation engine, and they’re all stupid.
Personalisation is effective. I've tested enough personalisation campaigns to be convinced.
And as a counter argument to Youtube/Instas algos. The reason TikTok has become so popular is that it simply better at personalising content, than say instagram reels.
I suppose it helps disambiguate that from the content around which ads appear. Beyond that, I suppose language is no less subject to fads and trends than any other realm of human endeavor.
My earliest memory of struggling with this kind of language was in high school economics class. I was forever put off from the material by the confusing truncation of noun-phrases into adjectives.
And it's a shame, because there's a lot to discuss here: vast swathes of the technology industry hinge on the subjects discussed. Weinberg and Lombardo seem to be suggesting that an emperor has no clothes.