How 2 hyper-growth companies are using Mixpanel to power and improve their data operations
When a company reaches hyper-growth mode, it’s worth taking a look at how it got there. In many cases, businesses that place data and insight at their core are the ones that are thriving. Forrester reports that insight-driven businesses are growing at an average of 30% each year and are predicted to take $1.8 trillion annually from their less-informed industry competitors.
Below are two stories from two leaders at growing digital companies that offer examples of how integrating data-informed practices into their operations, including mature product analytics with a platform like Mixpanel, can lead to success.
Using product analytics to power smart, lean growth at Immobiliare
Paolo Sabatinelli, Chief Product Officer at Immobiliare
Immobiliare is the number one real estate portal in Italy and a presence in 10 other European countries. Launched in 2007, over 7 million active users spend over 300 minutes per month on its website and mobile app. Paolo has been at Immobiliare for just over a year, having previously worked in product roles across sectors.
If you are a growing business, it’s common to add more people–more developers, more designers, more product managers. But at Immobiliare, we’ve found that optimization through new technologies is the best way for us to scale our operations. Because of this, our founder is aware that we need to invest in things like product analytics in order to be one of the best platforms in Europe.
The ratio between engineers and product managers or designers in our company is very high. My product team is small, which ends up being great because I don’t prefer to have an overly large team with multiple layers. But this means our product managers need to be responsible for entire areas of the platform, and the way we get it done is by leveraging product analytics, among other tools, to get sophisticated product user insights with very little lift.
What does this look like? We have Mixpanel working as the entry and exit point of the process of defining our product team strategies. For example, we can identify multiple user segments based on multiple use-case areas and pinpoint different objectives for us to be successful with those different segments. From there, we have the capability to match those objectives to the overall key metrics we want to achieve as a product.
One of our objectives is to move more traffic from mobile web to mobile apps—a common dilemma. Each set of users requires different tactics and key results. Mixpanel is a kind of master, guiding the other customer engagement platforms in order to execute these actions.
Putting product analytics into action
We started targeted campaigns using cohorts generated in Mixpanel that went on to be distributed through customer messaging. Our focus was on power users—our users who’ve identified as being really interested in buying a house. We then created a campaign only for the power users with a specific message that tells them a dedicated story and defines a dedicated value proposition—all meant to welcome them to download our app. The conversion rate of a personalized campaign like this is much higher than a generic “download the app” campaign.
I asked our engineers how long this campaign would take without Mixpanel, and they said it would take one year before being able to arrive at that level of personalization. Simply put: We wouldn’t be able to sustain our level of growth without Mixpanel.
How data-smart Ornikar finds value in self-serve product analytics
Aurélien Rayer, Chief Data Officer at Ornikar
Ornikar is the leading online driving school in France. The business provides education, a booking system for exams, the ability to organize in-person lessons, and competitive car insurance rates. It raised $120 million in Series C funding last year and now has over 200 employees. Aurélien has been at Ornikar for two years, having previously held senior data roles in a number of other businesses.
The place that data occupies in Ornikar is quite unique compared to other companies of similar size. Here, it’s represented in the strategy committee rather than sitting under technology, finance, or operations. Across different teams in the company, we have very experienced stakeholders that are mature on data topics, very autonomous, and doing their own analysis. That helps us to achieve our goals much quicker because it’s much easier to help them understand what we want to achieve and what our value proposition is.
On our product team, Mixpanel helps the most with this data autonomy by giving product managers self-service access to product analytics. We’re also now integrating all the Mixpanel data internally and mixing it with all our other sources so that teams across Ornikar can make use of our product data, as well.
Analyzing front-end data with Mixpanel
The biggest challenge we face today is the fragility of front-end data. To simplify, we have front-end data gathered, in part, by Mixpanel, and we have back-end data (production data) gathered by the tech team. The back-end is very strong, but the front-end is very weak because you can drive regressions very quickly. A front-end developer could update a library and merge it into production and our whole tracking system would fail.
Tooling-wise, Mixpanel helps us maintain front-end data trust, but there is also a people factor to this: We need to onboard and inform the tech team that front-end data is as important as production data by demonstrating its value. For instance, if we want to use data to fuel machine learning products, then it can’t break after a production release. We need to work closely with the QA team to ensure we don’t generate regressions—we need to have a level of trust built within the data.
When it all goes well, we can do great things. For example, we recently revamped the whole subscription process at Ornikar to generate leads. To get there, we used self-serve data to analyze all the steps that a user had to undergo during the process, detecting the drops and the pain points in the experience. That allowed the whole product team to take part in designing the best subscription process we could to drive conversion. It’s a direct application of leveraging the front-end data from Mixpanel.
Takeaways
Define and align product and growth
Using product analytics often blurs the line between product and growth or marketing teams. The companies we spoke with advise giving each team specific roles while using data to keep them directed toward a common goal.
“Our company-wide objectives align around one given KPI or target,” Aurelien Rayer mentioned. “Then all the different roles within the company are aligned towards that objective. So the product roadmap is integrated with the marketing remit and the data remit and so on. The mindset is that everyone works to the same target in order to grow the business.”
Ornikar and Immobiliare use product analytics to prioritize and maintain data awareness across both teams. By doing so, they’ve been able to focus on growing the company instead of dividing labor.
Use Mixpanel to save time, money, and effort
Processing and interpreting data can take more time and effort than its worth for your product and engineering teams. Both companies found that using Mixpanel is far more efficient than relying solely on a data analyst (or data team) for metrics.
Sabatinelli: “Having a data analyst within a squad or a team is adding more complexity, and you often have shared people with multiple teams. Before doing an analysis, you need to wait to prepare a set of requests and so on. This slows down the brainstorming process to gather ideas…and it’s also an additional cost that we could better use on investing on the platform.”
Rayer: “Our role as a data team is to centralize the usage of product analytics data so that marketing and other teams can use this kind of data the same way for their goals. And because our marketing spend is huge, if you use the data to reallocate budgets, then we can save millions with just a small amount of re-atttribution.”
Develop a culture of data accessibility
To follow that last thought, product analytics is only helpful if it can be widely used. Both Immobiliare and Ornikar make data accessibility and availability a major part of their operations. From the strategic level down to the operational level, both organizations employ tools like Mixpanel that help empower everyone to make data-informed decisions.
Sabatinelli: “Everyone uses Mixpanel! To me, a product manager and a product designer have to be completely independent and savvy in being able to analyze the behaviors of users.”
Rayer: “Our product managers get a lot out of self-serve product analytics, but we also have analysts who work closely with them and front-end developers to analyze Mixpanel data, review the setup, and work toward clean and robust tracking data… Making sure teams have the support needed to be able to easily and frequently access data goes hand-in-hand with our company’s quantitative mindset: Data is a key factor for driving all decisions that we make today.”
This blog was written in conjunction with Candyspace, a Mixpanel partner who supports ambitious companies investing in growth. Candyspace’s specialists have helped companies like Mars, ITV, Rolls-Royce, Nintendo, and Mazda bring the right product solution to market at an enhanced pace.
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