Data, business, sales, insights, and revenue are popular keywords found in abundance around the internet these days. As a Founder of my own company, I can certainly understand the need to focus on such keywords in daily, weekly, monthly, and quarterly discussions.
But, as a Data Analyst, not all keywords are created equal for each role in the company. Let’s simplify and break the business hierarchies down to three levels, which have a direct impact on how data can be used:
- Executives: The top of the chain that defines long-term strategy, implementation, and overall decision making.
- Manager: The mid-level staff responsible for action of strategy, interfacing between the needs to the subordinates and the Executive teams.
- Operational: The largest population of the business with the responsibility to make it happen by pushing the buttons, interfacing with customers, and carrying out decisions hour by hour.
This three tier pyramid of decision making in a business is streamlined to illustrate key areas that any serious Data Analyst should have Continue reading
One of the keys to getting customers hooked on your SaaS product is offering a free trial. Letting someone experience your product for free for seven to thirty days is a great way to establish trust with the potential customer, let them experience the product, and also gain insight into how they will use the product (customer segmentation).
On a recent project, I was reviewing data for a client and noticed a very interesting pattern in the login histories (not really, but we will call it logins since the real data can’t be shared) for trial users. This particular client offered a 7-day credit card trial with auto convert to a selected plan (i.e. monthly or annual). What I expected was a nice curve from day 1, declining each day, relatively smoothly and then an increase in logins after conversion.
However, after summarizing the login data for the first ten days of service (including 3 days for the auto convert), I found a sharp decrease in logins from day 1 and day 2, as well as a blip on day 6. See the chart below.
What was even more fascinating is how the other analysts and “experts” at the company interpreted this data. Some of the comments are below:
- “Wow, people pay us and use less?” – referring to the drop is usage on day 8 after becoming a paying customer
- “Those auto convert reminder emails are working, driving usage!” – referring to the increase in logins one day prior to trial end on day 6
- “Looks like we need pay per login” – referring to the sharp decline in logins from day 1 to day 2
- “If we can get the customer to use beyond day 4, we have them!” – not sure how this really fits in as we haven’t correlated logins with LTV, yet
- “People are cheap” – referring to the people logging in on day 6 to use the product prior to cancellation
- “If you are going to login to cancel your auto convert on day 6, wouldn’t you try the product one last time?” – again, referring to day 6
The chart is quite simple, a single line with 10 data points. What isn’t simple is really what this data means. In fact, I don’t think we can make a decision directly from this data. Rather we need to further understand what the trial users are actually doing on day 6 and how users with logins on day 7 compare to the users on day 1 (is this a bad a marketing channel). It would also be great to dive into patterns of logins just prior to churn or trial cancellation.
What fascinates me the most, is not only the different perspectives on the data, but the deeper questions that come out of the data. Data and customer insights are evolutionary. The more you know, the more you ask questions and the more the decisions and knowledge evolve.
Innovation is the key to staying and/or getting ahead in the marketplace. Innovation is simply a new idea, product, or method of doing something. How do you create something new? Checkout the following venn diagram:
Apologies, this is going to be more of a rant than a tradition blog post.
I had the pleasure of speaking with someone this evening that had the worst attitude of anyone I have ever met. For the sake of brevity, let’s boil the conversation down to this simple exchange:
Person: “But who is going to pay me to travel the world and hike?”
Me: “The people that are interested in your adventure, blog about it and tell your story.”
Person: “Everyone blogs about their adventure, no way.”
Me: “Yes everyone blogs about their adventure, but you have to speak with a unique voice and from your heart and they will follow you.”
Person: “I don’t want them to follow me. Don’t they have better things to do than read my hiking blog?”
Me: “Let’s back up… you want to hike the world and have someone pay you for it? You have lots of options…”
Person: “Right now, I need a better job… ” and the conversation continues.
With everyone of my explanations, this person had a negative reason why they couldn’t do it. They already failed at their dream within two sentences.
Dreams are goals and attitude gets you to those goals. Are you willing to work toward your goals/dreams? Is life half empty or half full?
Its your life, you decide what is important when you speak.
The perfect chart can convery a world of meaning on two axis.
The perfect chart contains no more than five categories.
The perfect chart launches a discussion of action.
The perfect doesn’t contain fuscia.
The perfect chart doesn’t exist as a template in MS Office or iWorks.
The perfect chart has clear patterns that are clear as day and night.
The perfect chart is as beautiful as the Mona Lisa.
The perfect chart doesn’t exist for 90% of the publications on the market today.
The perfect chart leaves you awe-inspired.
When was the last time your reporting department produced the perfect chart?