Building Your Analytics Strategy for 2015

2015 strategyAs we approach the holidays, our thoughts are turning to 2015 and how we can make the next year even better than the last. A lot of this starts with measurement.

Customer data is one of your company’s most important assets. Approaching it in a thoughtful way and with a clear strategy enables you to see real results. Here are five key points to keep in mind when creating your analytics strategy for 2015.

Start with Goals

Your analytics activities can contribute to your higher level goals if you plan accordingly. Begin by identifying the higher level goals, and then break each one down into specific and measurable parts.

For example, let’s say your department goal is to increase revenue by 50%. You can break this higher level goal into smaller (and again, measurable) parts, such as:

  • Optimize Conversion Process: If we optimize the conversion process by 10%, this will contribute X dollars to our revenue
  • Improve Retention: If we decrease churn by 15%, this will contribute X dollars to our revenue
  • Improve Campaigns: If we improve campaign performance by 5%, this will contribute X dollars to our revenue

Breaking down your higher level goals into smaller, quantifiable goals is crucial as it gives you actionable steps, while also keeping you accountable to your team and to yourself.

Leave Room for Exploration

While you should always start with quantifiable goals, it’s equally important to keep the door open for exploration.

Often with analytics you stumble upon a small hint to a larger problem, then dig deeper into your data for more insight where you uncover another hint, until finally you discover a major insight. This kind of exploration, while not planned, often gives you answers to questions you didn’t even know you had.

For example, watching Customer Profiles in real-time is a great way to diagnose usability issues you weren’t aware of. A user who spends an unusual amount of time during check out, hits the signup button repeatedly, or attempts to implement a setup step multiple times, may be an indication of a larger problem.

Similarly, when viewing an analytics report, breaking down a given metric to the list of corresponding users can provide a tremendous amount of insight. For example, if you’re wondering why a certain segment isn’t converting well through your funnel, spend a few minutes exploring the profiles of those users to uncover potential explanations.

Track the Right Data

All analytics start with tracking. If you’re not tracking the right data, you won’t get the right answers.

Make sure you have the correct data to be able to meet your goals. For example, if you’re going to be measuring conversions, make sure you’re tracking all the steps that lead to your conversion goal. The more granular, the better. The smaller steps in between the larger ones allow you to dig deeper and accurately pinpoint problem areas.

In addition, make sure you’re tracking the right properties for each event as well as user properties. This will allow you to refine and compare segments.

For example, you may want to compare how well users from different sized companies convert to your highest level plan. To do this, you would need to make sure to track properties, such as:

  • User Property: “company size”
  • Event Property: “plan level” for “payment” event

It’s generally better to err on the side of caution when it comes to data and track too much, rather than not enough. Once an event has been committed, there is no way to go back and track it after the fact. While you may not use the data today, new questions will arise in the future and you won’t be able to answer them without the right data.

Centralize Your Data

The more data you collect, the more important it becomes to centralize and streamline. There is nothing more detrimental to measurement and customer experience than fragmented and inconsistent data.

Make consolidation a part of your analytics strategy in order to give your entire team a single set of consistent data that can be applied across the board. This is important in creating customer experiences, which brings us to our next point.

Use Data to Power Customer Experience

You can do more with your data than measure. Use data to target, personalize, and create all around better customer experiences.

For example, you can use your data to display tailored content to users based on their past behavior. Similarly, you can prioritize help desk tickets for users who perform specific actions. Both of these examples leverage data to get the right message to the right customer at the right time – the foundation of good marketing.

Don’t underestimate how powerful your data can be. When organized and applied properly, data can be an integral part of meeting your goals.

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