“What people think of at the moment of discovery is really the discovery of the question.” – Jonas Salk
- 1. What is the ROI from your Facebook Ad campaigns?
- 2. What are the most popular actions users complete before leaving the app?
- 3. What are the top 10 countries that have generated the most revenue on the site?
- 4. What is the right number of emails to send to users that maximizes their engagement yet minimizes churn?
- 5. What is the “content stickiness” of various types of content from the site?
- It All Starts with the Right Question
What are the 2 main qualities a scientist needs in order to do something truly great, such as develop the first polio vaccine?
They are probably:
- An insatiable curiosity
- Strong critical thinking skills
Data scientists should be able to identify with Salk, since those two qualities are essential in their work, as well. Another important quality a good data scientist needs is business acumen. Good data scientists understand that it’s not only about conversion rates, numbers of newly acquired players and amount of revenue (although these measurements are very important). It’s also about taking a step back and asking:
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- Why did players convert more through one channel or campaign than another?
- What is the optimal user path to a particular conversion?
- Which users are your most valuable, and why?
But now, with the fields of online marketing, data science, and web analytics slowly merging, businesses must learn how to ask and find quick answers to the most important business questions, so they can maintain their competitive advantage.
Here are the types of questions business should ask and quickly answer to encourage growth and better customer loyalty:
1. What is the ROI from your Facebook Ad campaigns?
Businesses have data on their campaigns located in various internal and external databases, as well as in different advertising platforms, email marketing systems, and CRMs. An agile query language that is able to query raw data over time across these platforms can unify this data, including data such as users’ LTV cross-referenced with customer acquisition cost (CAC).
2. What are the most popular actions users complete before leaving the app?
The ability to discover the behavioral path your users take towards any particular action, especially a conversion or an exit, is vital in understanding how you can achieve higher business growth. If, for instance, a business discovers that most of their users leave the app after registration, they might experiment with encouraging registration later in the user journey, or test whether they can offer a simpler registration process. They may find that either of these may contribute to a better customer experience and higher rate of user loyalty.
3. What are the top 10 countries that have generated the most revenue on the site?
Time-series behavioral analysis allows businesses to query data from internal and external sources and analyze it over time. Once businesses generate a list of countries with the highest revenue, they can drill down deeper to discover particular campaigns, users, or even channels within those countries that are the most valuable. In response, they can optimize their marketing budget. The goal is to focus marketing budgets on users, countries, channels and campaigns that generate the highest revenue.
4. What is the right number of emails to send to users that maximizes their engagement yet minimizes churn?
Another valuable application of time-series behavioral analysis is the ability to find the sweet spot in an email marketing campaign: the exact number of emails to send customers each month before they think about unsubscribing. An agile query language can take the average number of emails sent, and combine that with the number of unsubscribes, clicks, and open rates to figure out this magic number. It’s a way of measuring the business impact of monthly emails on customer engagement.
5. What is the “content stickiness” of various types of content from the site?
It’s not just about the type of content your users consume. It’s about the type of content that keeps them returning repeatedly to your site. Beyond measuring the number of a user’s unique page views in a single session, behavioral analytics allows the joining of customer data from multiple platforms, sessions and devices to gain a clearer understanding of how customers behave on your site. Combine this data with content category and author, and businesses can start to measure which type of content brought customers back repeatedly – also known as “content stickiness”.
It All Starts with the Right Question
These are just a few examples of the types of questions business must be able to ask and find quick answers to in the competitive online world. Curiosity and business acumen are qualities that will take you halfway there. For the second half of the way, businesses will need an agile query language that is able to analyze behavioral data over time. Together with these characteristics and the right technology, businesses can ask and quickly discover answers to any questions they have about their customer behavior.
