|(Scene from I, Robot. image source: https://i.imgflip.com/fwri0.jpg)|
- At what rate are we losing existing customers (churn)? à can highlight product-market fit issues, education issues, misaligned expectations, complex UI/ UX, etc.
- What is the lifetime value of a customer? à help determine the ROI of marketing strategies, especially against the cost of acquisition
- What is our server uptime service level? à understand if service levels and how that may impact existing customers
- How often are our users using Feature X? For how long? à help determine roadmap and UI/ UX issues, unnecessary feature sets, etc.
- How are we acquiring website visitors, and at what rate are we able to convert these visitors to some call-to-action? à test the efficacy and messaging of marketing efforts
- How often are users visiting our knowledge base? Is there a particular article that is visited most often? àbetter upfront knowledge sharing/ education, better UI/ UX opportunities
Goals and strategy of the company leads to questions on where the company sits today, and how to achieve tomorrow. Then, instrument as needed to capture status and improvement.
- Metric: a standard for measuring or evaluating something, especially one that uses figures or statistics
- Instrument (-ation): a means by which something is effected or done; a device for measuring the present value of a quantity under observation.
- Average speed
- Heart rate
- VO2 max (lung capacity)
- GPS (for distance)
- Heart rate monitor
- Stopwatch (time)
- Metabolic cart (VO2)
- Cost of acquisition. This is cost to capture an unaffiliated buyer. Need to know the costs associated with closing this opportunity including marketing costs, engineering support, etc. For this metric, it’s important to track the flow and behaviors of a customer through websites, sales touches, etc.
- D1, D7, D14, D30 retention metrics. Here, D stands for “day” and the number refers to the number of days since a user first enters the system. This metric tracks the percentage of returning users to the service in D days –gauge “stickiness”.
- Open and Click-Through Rates of Emails. Many products these days have email engagement and nurture campaigns. Here, companies measure if users are opening these emails and, if applicable, are they clicking into a destination the company is looking for.
- Drop-off During Sign-up Process. Many products have multi-stage sign-ups which can deter and annoy users from completing sign-up. By measuring here, the company can quickly ascertain if the sign-up process needs to be simplified or be very valuable to motivate complete sign-up. If they never enter, they’ll never see the great product! (This, by the way, is why so many apps use Facebook, Twitter, Google login… plus, companies get personal data shared from those platforms.)
- In-App Engagement.This is a big bucket including what pages, tabs, profiles, features are viewed and used. You want to understand how users interact with the product – are they finding pages useful? Are features cumbersome?
- Customer Lifetime Value. Same concept of the revenue of a customer (or net profit) but extrapolated against the number of times a customer buys (subscription, multiple products, etc.).
- Churn.That is, what percentage of customers stop buying annually? Good annual churn for SaaS businesses according to Sixteen Ventures is 5-7%. High churn may point to poor value, mismanaged expectations, or an inherent problem in the product.
- Average Revenue per Customer. To be explicit, it’s total revenue divided by customer. In this case, revenue would naturally be weighted by where most of revenue comes from.
I get excited when a company properly instruments their products and services. It demonstrates tremendous maturity and understanding to recognize engagement data will drive confirmation (or rejection) of hypotheses, and thus, enables smarter business decisions.
- Fullstory– records behind the scenes how users interact with a site or app that can be replayed later. You can see where a user hovers his mouse, scrolls, stays on some block of text, etc.
- Unbounce – taking A/B testing to multi-variate testing for landing pages. Quickly set up a landing page with multiple variants, and Unbounce automatically directs visitors and tracks conversions.
- Pardot – Easily send automated mass messages personalized to recipients based on where users are in the sales funnel. Tracks users from first site visit and beyond for nurture campaigns
- MixPanel/ Intercom – Very different in how each operate, but the feature I liked most was being able to trigger specific messages (more granular than Pardot) based on user interactions. High-degree of control by building out event-driven rules and trigger notifications.
- Kevy – Marketing automation for ecommerce stores. Slick tool to understand consumer behavior and enables stores to better market to consumers by offering coupons, messages, and the like based on rules and triggers.
In gist, there are lots of tools available for instrumentation with overlapping features. It’s fun learning about these tools now, and dreaming of how great these would have been at Body Boss. Though, several tools didn’t exist three years ago… inherent problems don’t change, but solutions do.