What we learned about the smartest companies.
We took a look at some of the smartest companies to see what makes them tick. Unsurprisingly, we found that many of them are making a huge impact with disruptive technologies and driving growth with lean startup methodology. But we started digging deeper, because we wanted to know — how do they make something truly awesome that attracts so many loyal customers, advocates and devotees?
Money certainly helps, but there had to be something special going on at these companies to attract it. Having a team of bright minds is a huge asset, but there are so many influencer opinions, and there’s no lack of growth hacking strategies, so each organization uses differing strategies. Great tools also help, yet there are so many tools, services and platforms being used, we began to feel that there must be something more fundamental to their success. There had to be some common thread among these stellar players.
Sure, they’re all great at design, development, digital marketing strategy, and watching their metrics. And many of them are using some form of the latest marketing automation systems. But why are they so successful when many competing companies have similar assets?
We found one significant similarity — all the smartest companies work relentlessly to continuously improve their value to customers.
So, then came the next question. How do they do this, and do it so well?
We began reading articles, studying industry analyst whitepapers, and even spoke directly with over a dozen company executives about their intense focus on the customer. It turns out that most of these companies are using the same iterative, incremental improvement processes, defined by agile methodology, that developers have been using for years. They’re now using this data-driven, experimental testing process to optimize all their customer touchpoints — beginning with their marketing and acquisition strategies all the way through to customer support.
Driving this process is a laser-like focus on a narrow set of key indicators, and analyzing how their customers react to testing ideas for improvement. At the core, are simple feedback loops. By using accurate, focused feedback developers and marketers are able to hypothesize improvements, create experiments, and gain insights from user activity at a high tempo. The outcomes spur further experiments that optimize the way customers interact with their product or service. It becomes a continuous cycle.
Accurate, focused feedback enables developers and marketers to hypothesize improvements, create experiments, and gain insights from user activity.
Next, we began to explore the nuts and bolts of these customer feedback systems to determine how they are set up, what data is collected, what systems they’re using, and how they’re able to glean actionable insights. Typically, the last thing teams need is more data and reports. And what makes these companies able to integrate this process into day-to-day activity that people actually use?
We discovered that the tools didn’t matter as much as defining the process. From the start, the process is built upon a clear understanding of their company’s critical business drivers. For a majority of these companies, it’s three things: acquisition, behavior, and outcomes. These companies have become very good at analyzing what works best to acquire customers at the lowest costs, learning what moves users through their journey toward conversion, and identifying what keeps their customers engaged.
It’s three things: Acquisition, Behavior and Outcomes
We recently attended an event hosted by Segment.com named Analytics for Good, where Watsi, a nonprofit that funds healthcare for people around the world, opened up their data to top analysts from several companies including Chartio, Looker, and Mode. This helped to give us a glimpse into how some very smart companies analyze customer data to find insights.
As a SaaS-based company, Watsi sought ways to optimize their activations (acquisition), retention (behavior), and conversions (outcomes). You can read Segment’s summary of the analysis and recommendations here. What transpired was a process of “analytics, experiment, analytics”. Perhaps more clearly, Benn Stancil summed up his method:
1) Look at what’s working
2) Figure out if it’s repeatable
What sets many of the smartest companies apart from the pack is their ability to create those ‘aha moments’ where something insightful can really make a difference. In Watsi’s example, analysts started investigating spikes in the customer data, and found that corporate Gift Card donations could actually drive 300% growth by getting users who redeemed the cards to sign up for the universal fund. Huge!
OK, so we see how the process works, and why the smartest companies use it. Now, as in the words of Benn Stancil, how can we make this process repeatable? Most companies don’t have the resources to hire analysts with planet-size brains, much less open up their data for the world to see.
We work with some great tools in the industry that provide metrics into customer behavior. However, it’s difficult to implement a ‘one size fits all’ tool into cross-team processes that consistently provide valuable insights. We sought a process that’s easy to set up, flexible, and will actually be used both by individuals as well as across teams.
We began looking for some inspiration.
We love Rob Sober’s concept of marketing stacks and ability to bootstrap several tools to measure how customers are engaging with his SaaS called Munchkin Report. With his marketing and analytics stack, he is able to see trends in his key metrics, and act (and even automate) upon that information. Most importantly, Rob struck us with this statement, “laying a solid foundation for analytics and marketing automation takes foresight and planning, some technical chops, an analytical mindset, and some trial and error.”
We also looked at some great emerging services that allow companies to skip the breadlines, access data directly, and gain valuable insights for themselves with ever increasing ease. However, while certainly promising and helpful for deeper analysis on specific problems or identifying opportunities, we felt that mass access to raw data could lead to data overload, and distract that laser-like focus on the customer.
Then we re-discovered some interesting articles. For several years, we’ve been inspired by Jake Peterson, who is now Head of Customer Success at Segment, with his Dirty Analytics blog posts. His article on Analytics is a waste of time is telling. We love his philosophy of keeping metrics simple, and measuring only what matters.
The key to not wasting time with analytics is to be conscious of exactly what you need to know before digging around inside of a bunch of tools.
We have found this rings true in our experience. And it underscores the benefit of the process used by these smart companies — they know exactly what they need to track. Before any of the tools, before the data, before any dashboards are created or reports are run, they create a framework of the business critical customer data they need to make decisions. Jake goes on to challenge businesses to choose their One Key Metric (OKM) that’s most important, and a handful of key metrics to support valuable insights.
That OKM, and a few key metrics is certainly good advice. Yet, in our experience, it really depends on the company, what stage of growth they’re in, and what’s needed at each stage of a customer’s journey. There are also metrics that mean more to one team versus another. Marketers care more about which channels and campaigns drive the most valuable conversions, while developers care more about about user behavior on their apps. However, the important takeaway is the need to create a narrow set of key indicators.
At this point, we had several building blocks with which to experiment in building a repeatable model. Next, we put these insights into action.
We began with a discovery process by asking our clients about their goals and “who, what, when and why” something needs to be tracked. If the reason they gave was not directly tied to improving customer value, or a core business driver, it was either pushed down the list or eliminated. For example, we removed all vanity metrics. In addition, we removed tracking anything that did not contribute to actionable insights.
We took this list and organized it into a Tracking Plan. The Tracking Plan served as the client’s master spreadsheet of who, what, when and why something is being tracked — tied directly to the key business drivers. The plan was shared with each stakeholder so that everyone was on the same page.
Using the Tracking Plan, we’re able to create tracking code for the events and views that we needed to track using analytics.js, as well as the tags needed to deliver the data on channel campaigns. Providing all the tracking code at once to developers made it much easier to go into their websites and application code, and insert them where needed. An organized tagging system also made it easy for inbound marketers to add campaign tags.
Once the data begins flowing, we consolidated that data collected from all the team’s tools, and organized reporting with visualizations on dashboards by role. By displaying data based on the pre-determined KPIs and supporting metrics, and including target goals in the graphs, it became instantly useful. Teams were then able spot potential problems, overall trends, and investigate spikes in their data much more quickly. In short, teams began to experience more of those aha moments.
In practice, we’eve now found that the Tracking Plan has become an indispensible tool for insights, driven directly by the key business drivers focused on the customer, into a tool that’s used daily. The plan organizes the creation of tracking code & tags, connecting tools for data consolidation, and the delivery of role-based data visualization that provide a the means to quickly spot actionable insights that made teams more productive. The Tracking Plan became the star around which everything orbits.
The Tracking Plan became the star around which everything orbits.
What we learned from the smartest companies, and their relentless focus on continuously improving customer value, is the need for a process that drives continuous insights. A great Tracking Plan can accomplish this as it:
1. Identifies a company’s objectives for acquisition, behavior and outcomes
2. Determines a short list of what’s tracked by asking Who, What, When and Why
3. Enables the tracking code and tags, and where to add them in the code and campaigns
4. Guides data consolidation, and data visualization to deliver actionable insights
5. Supports the iterative optimization process with high tempo feedback on experiments
The beauty of the Tracking Plan is it’s simplicity, ability to scale with growth, and requires just a single shared spreadsheet.
At it’s core, is really a model for a set of feedback loops that can be implemented into any website or mobile application. The feedback model is tool agnostic, and it enables teams to rapily experiment, iterate and optimize. It’s a model used by the smartest companies to continuously increase value to their customers and drive growth.
For our purposes, we’ve decided to give it a name — Active Analytics Loops
We hope that our research and experimentation into creating a repeatable process that provides valuable insights from customer activity will help you. You’re welcome to share #ActiveAnalyticsLoops. Regardless of our name for the model, we hope this information will inspire you to put into practice a similar framework and process that will organize your activities around acquiring and optimizing value to your customers to drive growth.