Data Products: Tell Me Why
A data product’s main ingredient is in the name, it is data.
In this article, I’m going to give my take on data products and why they’re so important in creating value for companies. This is part of a series, where I’ll follow up more specifically on what they are and how we make them.
As a product manager, it’s only right that I start with telling you why data products, because we ask that a lot, and this couldn’t be truer:
Having a young child, the reference to ‘4 year olds’ couldn’t be truer either, I’ve recently started playing why back… just because.
Data Products, everywhere
In your everyday life, you’re interacting with data products all of the time, or shall I say they’re interacting with you. So to start, let’s focus on some of those to bring to life what a data product is, and you’ll see why they’re important for the company building them, and for you as a consumer too.
You sit back to relax for the evening and Netflix suggests a movie it thinks you’ll like 🍿 … that’s a data product right there, the recommender. It’s taking everything Netflix knows about you e.g., shows you’ve watched, and looks at you against someone like you, and suggests shows.
Netflix value creation: This increases the stickiness of Netflix, makes you come back time and time again as it’s relevant. All of this means Netflix retains you as a customer for longer, protecting their revenue, and when they put the price up, you’ll be happy to pay it because you couldn’t live without it.
You prepare your space for cooking up that spaghetti bolognaise, but first, wine, and some tunes. Spotify’s daily mix is made for you. As above, a recommender. It’s learning what you like, and better yet, if you’re in the USA 🇺🇸 or Canada 🇨🇦 you’ll be able to experience a DJ laying down the tracks you’ll love most. Your very own party. Spotify takes in what you listen to, when you listen to it, and if you skip before 00:30 seconds, then it’ll take that as you weren’t really into it.
Spotify value creation: really, this is the same as Netflix, but I’d say Spotify’s recommendations are absolute killer. This again is about stickiness, customer retention. My ‘liked’ playlist is almost at 1000 songs now, and the variety is real. Spotify knows me, so when I hit up a radio it’s always a winner. It knows so much about my taste now (varied!), that it’d really hurt me to move to Apple Music.
You’re debating your commute home by train or taxi 🚕, you open the Uber app, enter your destination and you’re greeted with a price. This price is especially for you, with love (commission). Stand next to your friend, put the same destination, bet your price will be different 🙃
Uber value creation: stickiness for the convenience, no need to call a taxi company at a loud venue, or pay cash (although most take cards), you know who you’re riding with… but from the company side, dynamic pricing is a big one, and it’s how they make money, particularly when demand rockets, or when there’s little supply, either way, value is created through optimising the price and customers coming back as it’s convenient, not cheap. Convenience and cheap don’t seem to go together, ever, that’s the premium we pay for.
You need to be in the office for 9am, so you want to check what time to leave to arrive by then. There’s a nifty little feature that tells you when you need to leave by, a prediction based on lots of data including traffic on that particular day of the week, and maybe events happening in the area. Thank you Google Maps 🗺
Google Maps value creation: theme, stickiness, I mean, I am so loyal to Google Maps. If anyone starts getting Apple Maps out, I’m like absolutely not… customer retention here again, and of course data data data. You not only buy into this part of the Google ecosystem, but all of it, one of the most effective platform players of our time.
So there you have it, data products are everywhere. Companies that are providing super experiences, retaining customers, growing their market share, and looking good on FTSE or S&P for example, they are innovating with their data. They’re building data products, and investing in the infrastructure and tooling to do bits in this space.
The common thread is stickiness, customer retentions and engagement, all of that equals more data, more power, more relevance, and nice stock price. These data products keep you coming back to the core product/platform itself, why would you pick a competitor?
The power of data
In the past, and even now, many companies, treat data as an insight and reporting mechanism, to inform what happened in the past. Data is the moat for lots of companies, it’s the competitive advantage, a critical element of the value chain, and futures rely heavily upon using data in the right way.
Typically, forecasts are based on what happened last year, insight comes, data teams intend to drive action, but how often do other teams ignore what’s right in front of them?
A classic is and always will be, the Blockbuster story. They obsessed over the revenue from late fees without looking left and right of that shiny thing, and I bet insight was provided to the execs and they ignored it. Feet up on the desk, or flying high on an exotic trip, they didn’t want to believe their current business model was being disrupted, by those putting the customer first, and applying data and technology. I’d go all in and say that they had the data, they had access to consumer trends (plus they were consumers, we all are!), they ignored it all and eventually they died.
Blockbuster lives on in memory, and this Twitter account gets me every now and again…
Disclaimer: I loved Blockbuster as a kid, it brings back a lot of happy memories. It’s a Friday night and I’d spend a good 30 minutes at least wondering around looking for a movie to watch, whilst my mom paid late fees from a movie we forgot to return on time.
Data is driving valuations of companies, and deals. Going back to 2022, the Barcelona x Spotify deal reduced in value rapidly because, of the 350 million Barcelona fans only 1% of them were registered with meaningful contact data.
You can’t flick a switch and have a data power house
If you think data’s easy, think again
If you’re working in data, or you’re someone asking for it, you’ll be familiar with, “fill in this table with the numbers please”. It sounds so simple, but for the person being asked, they’ll need to find the data (does it even exist in one place), run a query or ten, and then make sense of it all. That thing you asked for, could be available via 10 tables that have 20+ columns and 1 million rows. So be mindful of data people, and invest in their tooling and the skills sets to create the IKEA for your data.
Companies that aren’t investing in their data are missing out on delighting their customers and making better decisions, whether that’s operational decisions on the fly or manually, as well as strategic decisions. By treating data as an asset, and creating data products, you can see this as using customers’ data in a meaningful and of course, ethical way, returning it back to them as a useful product (DJ Patil).
Investing data isn’t about collecting more or cleansing it, you can do those things all you like, but if you’ve not invested in the people to create value from the data from making it available, to making it usable to creation value, then you’re way off.
By ignoring the true value of data, and the investment to handle data at scale, companies that haven’t taken this seriously have missed out to competitors, big companies that entered new places, well backed and startups that made a huge bet on solving a customer problem with the perfect fit. Industries have been disrupted, data (a blend of quantitative and qualitative) drove much of of this. In the two and a half years of our data true journey, I’m always taken back by how far we’ve come, it hasn’t been easy and it’s taken a lot of time and investment to get where we are.
Tell me more
Finding the why for each data product or platform, is not an easy job, but it’s a super rewarding one.
For me and my team of Data Product Managers, we’re in a unique position in my opinion. At our core we’re product managers, and we understand data and engineering, but we also part with domain experts to get to know their context, and how that translates into customers’ experiences with our company.
For too long, data teams have gone off and built what they think is the right thing, without any assessment or validation of what matters, who it matters to and how it’ll be used. Or in other cases, just focusing on reporting and basic insights. Data Product Managers bring vision, direction and a mission to data teams, which enables them to focus on what matters, creating value through using data in sometimes simple, sometimes weird and wonderful ways!
Why are we here?
A lot of what we do is driven by our Functional partners in various business units through discovery and validation activities, however, sometimes, and in recent times, new technology comes and we may spend a week doing some R&D, which leads to something… so whilst I very much agree with making things people want, sometimes, to drive a shift or take advantage of something new, we have to make people want things… and in recent times, we’ve done a good job of this, with ChatGPT, not for the fun, but for genuine business problems, where we can drive efficiences, and better customer and agent experiences. Let humans focus on hard, uncommon problems, and let machines do the other things, and continuous learn and get better.
I hope by now the why behind data products is clearer for you. In the next article, I’ll go into the detail of the what and the how. Follow me to see when it lands, and if you’ve got any interesting experiences to share, or you’re just getting started on your data journey, always happy to hear from you.
