Over the past few years, companies of all sizes have invested in tools to help manage and monetize customer data, including customer data platforms (CDPs), analytics, and experimentation tools. The value of these tools is clear to the product, data, growth, and marketing teams who use them daily. But for the folks who sign the checks in finance, the ROI may be unclear, the costs continue to compound over time, and they still ask you if you “really need this to get the job done?”.
In today’s economic downturn, CFOs are putting stack consolidation and cutting the cost of software at the top of their priority list in a bid to cut costs and improve efficiency. They’re evaluating user experience, functionality, and usage to determine the ROI of the tool. Even the mighty AWS is feeling the pain.
If you own the stack for your digital products, chances are you’re being told you need to cut costs. You’re likely being forced to take a closer look at the challenges and opportunities in consolidating your data stack. In my role at Amplitude, I speak with customers and prospects in the industry daily and have heard their struggles on this topic. In this blog, I’ve gathered what I’m hearing about consolidation and what you need to know.
It’s rough out there
Given the macro environment, we’re seeing our customers demand higher-performing, cost-efficient solutions to analytics, experimentation, and marketing use cases.
One VP of Product we spoke to recently said that they were “willing to make the users of these tools a little bit miserable” to get to the cost savings demanded by the C-suite.
At the same time, layoffs require teams to do more with fewer people, leading to the need for self-serve, easy-to-use tools. So what’s a team to do?
Although the VP I spoke to was willing to make their team “miserable,” I don’t believe that’s the inevitable choice you have to make when you go from “best of breed” to “all in one.”
As you consider consolidating your tools, you need to determine what you really need from your stack, and how your team will adopt it. And of course, these tools should integrate with your data warehouse and other investments, and they should have the following capabilities:
- Analytics: to provide customer behavior insights and helps identify opportunities for growth
- Experimentation and Feature Flagging: to validate product “bets” so you know they’re leading to your desired outcomes
- Activation: to be able to re-engage users through the appropriate sales, customer service and marketing channels
So, is consolidation right for your business?
Whether you are thinking of downsizing the breadth of tools or cutting time spent maintaining solutions, there are multiple ways to cut costs.
I recommend to customers and prospects to think of total cost of ownership as:
- License cost: How much money you pay a vendor for software is the first thing we usually think of regarding costs, but it’s not the only consideration
- Cost of adoption: How easy is the tool to adopt, and how many users can actually use it? Low adoption can lead to additional costs over time. For example, you may need a Consulting engagement to get the insights you’re looking for.
- Cost of implementation and training: How many engineering resources are needed to implement SDKs and data pipelines?
- Cost of data: How many copies of the data are you going to pay for?
- Cost of data silos: Do you have a holistic view of your customer or business?
- Cost of integrations: How many are out of the box vs. custom builds?
If you’ve taken a “best of breed” approach, you may have realized that it really means constant maintenance of integrations regardless of what vendors promise. Every integration is a potential failure point and that results in another copy of the data. You’ve realized you’ve continuously invested engineering time to stand up, integrate, and maintain data pipelines. It can be difficult to scale and costs compound over time. And with so many different tools to learn and use, your teams may have struggled with self-service adoption and your analysts are swamped with data questions. This slows down your teams’ ability to act on their insights.
With respect to homegrown solutions, which I see a lot of around experimentation, these are usually great at first but tend to be a band-aid. With constantly changing business priorities and resource availability, it is difficult to maintain a homegrown solution that still meets business needs. More and more companies are looking to outsource this function so they can focus on building their core product, instead of maintaining internal tools.
The way forward with Amplitude
Once you’ve decided to consolidate tools, you need to make sure it all works together, that it will indeed lower total cost of ownership, and be easy to use for teams across the company. (Again, I don’t think your teams have to be “miserable” when you consolidate tools.) Our customers have found the right path with Amplitude because we provide a single solution that meets the capabilities required to optimize your digital product:
- Analytics, experimentation, and activation all on a unified data platform
- The capabilities work both standalone or on top of data warehouse like Snowflake
- With natively integrated capabilities, your team can discover new audiences, and then seamlessly make them available across the Amplitude platform.
- Running targeted experiments or making the audiences available to downstream destinations like customer engagement platforms like Braze and Salesforce, is easy with no code integrations.
When Jumbo Interactive streamlined its stack with Amplitude, they wanted to make smarter product bets, faster. With product analytics, data, experimentation, and personalization in one place, Jumbo Interactive is able to fuel its growth loops, and see results—they’ve seen a 40% increase in monthly active users using their product, Lotto Party.
AllTrails was tired of maintaining a custom SDK for each platform, which required too much engineering time, and left them with siloed data that was hard to activate. By leveraging the Amplitude CDP, they are able to deliver personalized experiences and drive higher conversion rates without bringing on board yet another vendor. As Andrew Scarani, Manager, Data Science & Engineering at AllTrails said, “It’s less time spent fixing data issues, less time to start tracking new events, and less time integrating with downstream systems.”
Even just last week, Super, a virtual travel agent company we work with decided it was the right time to replace its homegrown feature flagging and A/B testing tool to keep up with its engineering culture of shipping fast and often. By adding Experiment to Analytics, they are streamlining their stack, improving data quality, and making it easy for marketing and other teams outside of product and engineering to run tests on their own.
Make the switch
As an industry, we have been here before, and in every recession, we evolve and grow. We learn to do more with less. Teams are scrutinizing every investment because right now, leverage is critical. I encourage you to evaluate what technology partner will have an outsized impact on your team and company.
We’re here to help. Let’s grow together. Even if you’re not looking to consolidate, Amplitude will continue to support integrations with the leading tools in each category. Get in touch – our team is ready to work with you to help you migrate off of other tools and consolidate on the leading digital analytics platform.