How Customer Event Data Turbo-charges Your Business

Customers... What do they like? What do they use? What kind of customers used my precious new feature? There are many reasons that any business should use customer events. Ultimately everything leads to two points: customer satisfaction and revenue.

Customer Event Data

When I first started playing with Google Analytics it was beautiful. A new world was in front of me. With only a quick setup I was able to see what's going on with my users. Many companies cross to more detailed questions and Google Analytics are not enough. There is a large amount of tools out there such as Mixpanel and KiSSmetrics. These tools helped us to easily create funnels and visualizations of how people are using our services. With Mixpanel, you may dive into your events, analyse them, discover trends or create weekly cohorts.

Essentially anyone on a team can run some analysis in a short amount of time.

At some point, you may need a Product Manager, an Analyst or Data scientist to answer more sophisticated questions. Questions like "What is the average time between action A to action B" or "How do custom segments of users behave in my product" or "What kinds of actions are most likely to lead to a sale"?

In many of these cases, you may need data from various other sources. For example, you may need to combine your specific data with data from sources like Mailchimp, Stripe or your transactional Database.

How do custom segments of users behave in my product?

Using the information with specific events will provide half the truth. The other half is to get the information of how to segment your users. For example, a segment could be:

• users from a specific email campaign. That will require user data from your email marketing service.
• or users that belong to your business customers. That may require to include data from a service like Stripe.

This will give you some insight into how segments of your users behave, and how to stir your product development.

What is the average time between Action A to Action B?

Ever wondered how long it took for a user to signup until to make a purchase? Or how long it took for a user to do make an action or do another? All these data are available, but you may need a separate layer on top or custom views to add your business logic.

What kinds of Actions are most likely to lead to a sale?

From the users that actually registered and paid for your service, who came from a webinar or an ad? Who was more valuable in the end as he made an up-sell.

How do I do it?

1. Get your data in one place.

One way is to get the data that reside in various places (eg email marketing, Ads, payment service, your transactional Database etc). Next, you may need to push everything to a data warehouse solution like PostgreSQL or Amazon Redshift or Google BigQuery.

If you have the development resources and time, you may build the data pipelines on your own. That means that you have to write, host and maintain a flexible data infrastructure. But it is not always the best solution as it comes with heavy maintenance and commitment from your development team. That will lead you to redirect valuable sources to something that is not your company's core business.

If you need something now without having to commit development resources you may use a self-serve product like IBM Watson Analytics.

2. Ask questions of your data

• A Product Manager or VP, start by applying a BI tool like Metabase or Watson Analytics from IBM and start asking and get answers in no time.
• As an Analyst, you will need only to think about the questions. Start writing the SQL queries that you need and then work with a service for visualization like Watson Analytics, Chartio, GoodData or Klipfolio.
• Or ask a Data scientist to start working her magic using R and SPSS Modeler to discover trends and build prediction models.

I hope you find this article interesting. If you would like to discuss better decision-making through Predictive Analytics and big data, please don’t hesitate to reach out to me at +61 405 753 468 or via InMail

- Chris

Source Link: https://www.analyticbridge.com/profiles/blogs/how-customer-event-data-turbo-charge-your-business