When does it make sense to build vs buy your analytics solution? What’s the best fit for your business? Data driven companies should think through the pros and cons of each approach.
Many companies have the expertise and experience to build analytics in-house and for eng teams it’s an interesting challenge. But with that challenge comes costs–both in building infrastructure costs and engineering time. Once it’s built the system also needs ongoing eng support to make sure it scales as the company grows–not an easy task— as well as to make sure data is being recorded correctly as your team builds new products and features.
In-house analytics tools require an in-house expert or building out a BI/Data team. These people will become the gatekeepers that extract the data, use SQL to run queries, and export to Excel. That process usually runs something like this:
Figure out which data is stored in which database. Most companies use multiple different databases.
Write the appropriate query–usually SQL–to download the data you’re after. Note that this query will need to be constantly updated to ensure you are collecting the right data points.
Download the data to Excel and build a custom, comprehensive analysis.
Share the insights from data via email or presentations.
This means the data lives off-line, siloed, unshareable, and out of date.
These elements are all part of the cost of ownership that most organizations tend to underestimate and why building often ends up being more expensive and much more time consuming than using a third-party tool.
With a tool like Mixpanel, anyone can run reports and everyone is referencing the same real-time data. Creating your own data store means marketing probably can’t use it, and any new hires will have to spend time learning the system. Mixpanel is easy to pick up in ten minutes, even for your social media intern. More widespread access to accurate data = better business decisions = growth.
When you build your own analytics you are much more likely to have data inconsistencies and make errors in your reporting that take longer to cover. Mixpanel has thousands of customers constantly vetting our calculations while you’ll only have a couple.
At the end of the day, we have seen people invest in building analytics tools only to end up utilizing a service like Mixpanel. We’ve even had customers come to us wishing they had gone with Mixpanel upfront, rather than wasting time and resources building in-house.
Companies look at the cost of building analytics in-house as simply the price of one engineer. In reality, there is a far more significant total cost of ownership associated when you factor in database maintenance, database upgrades, the variable time of a BI rep running queries and slicing data in Excel on an on-going basis. Not to mention increased risk of making decisions based on faulty and stale data, and data bottlenecks in an organization.