A Simple Way To Make Your Analytics Actionable

Business leaders want data reports and dashboards at their fingertips, so they can make informed decisions that drive positive outcomes. 

For example, if we know how many people visited our website last year, then we can determine whether our search engine optimization efforts are working.

If we know what percentage of visitors use a mobile device, then we can decide how to prioritize the user experience for small screen sizes.

If we know which social media platforms drive the most paying customers to our store, then we can decide where to increase our advertising spend to maximize return-on-investment.

Information is powerful. But, only if it’s actionable. 

Thankfully, there is a simple way to make sure your data and analytics are actionable. 

To get the most out of your analysis, you’ll need to document your goals, reporting structure, lessons learned, and actionable next steps. Think through the process in these four stages:

• Goals Set the Foundation for Your Analytics Work
  

  What is the purpose of your analytics? What metrics are important to you?

  Decide which goals are right for your business at this time. Tracking everything is a recipe for information overload and unactionable data!

  Goals should be clear and specific. If you have key performance indicators (KPIs), tie them to your goals so that you are on track to achieve broader business objectives.

  • E-commerce retail example: Increase website traffic by 25% in the next 6 months.
  • Construction company example: Reduce project timelines by 5% in the next year.
  • Restaurant example: Increase revenue by 8% next year.
  • Financial services example: Increase customer retention rate by 12% over the next two years.

• Reporting Focuses on What Happened
  

  Reporting should be objective and accurate. Providing a basis for comparison is a great way to provide context, but make sure to set forth your reporting processes and adhere to them to prevent reporting bias.

  • E-commerce retail example: Generate a report that summarizes traffic data, including traffic volume, traffic sources, and conversion rates. This could help identify areas for improvement in website design, user experience (UX), and advertising strategies.
  • Construction company example: Generate a report that summarizes project timeline data with high-level metrics, including average project completion time and a breakdown of each project stage. This could help identify frequent bottlenecks and areas for improvement.
  • Restaurant example: Generate a report that summarizes sales data, including revenue by menu item and average number of orders by time of day. This could help identify popular menu items, inform pricing strategies, and optimize staffing needs.
  • Financial services example: Generate a report that summarizes average customer value over time, including their location and financial products used. This could help identify popular products by location, inform marketing strategies, and enhance the lifetime customer experience.
  
  

  Using summaries, roll-up data, and visuals in reports will help set yourself up for success when you need to quickly glean data insights.

• Insights Explain Why Things Happened
  

  By analyzing reports from the first stage, your goal is to gain:

  • Understanding
  • Patterns, Trends, and Relationships
  • Conclusions

  Easier said than done. Gleaning accurate and powerful insights from data requires talent and a dedication to objectivity. So when you succeed in this stage, it’s natural to feel a sense of achievement… value has been delivered. The data is in your hands, and you know what it means. 

  • E-commerce retail example: Analyzing website traffic data reveals that social media is a key user acquisition source.
  • Construction company example: Analyzing project timeline data reveals that a certain stage of projects is frequently taking longer than planned.
  • Restaurant example: Analyzing sales data reveals that a specific type of menu item is being ordered more frequently than in the past.
  • Financial services example: Analyzing customer data reveals that long-time customers are more likely to use multiple products.

  After this stage, it’s time to take action.

• The Action Stage Defines What Should be Done
  

  For each stage of your insights, you may need to answer a few difficult questions:

  • Should we stay the course, double down, or change directions?
  • At what level (threshold) do we take action?
  • What is the related metric or KPI?
  • How can we make something else happen? What change options are available, and why are they expected to make an impact?
  • Will this action support our goals from stage 1? What results do we want to achieve?

  The action stage requires a recommendation of what to do, as well as someone (or a team) to execute. Make sure you know who is responsible for making recommendations based on insights. You may not know who is best suited to execute until a recommendation has been made.

  • E-commerce retail example: Based on insights from website traffic data, the e-commerce retailer could implement more social media campaigns to double down on the effective traffic driver.
  • Construction company example: Based on insights from project timeline data, the company could implement process improvements to streamline a specific project stage. This action could help reduce project timelines and improve profitability.
  • Restaurant example: Based on insights from sales data, the restaurant could implement new menu items to increase revenue and customer satisfaction, and adjust staffing throughout the day to match the busy hours.
  • Financial services example: Based on insights from customer data, the financial services company could implement strategies for cross-selling and providing discounts for customers using multiple products.
  
  

  Taking action on your insights is where you get value from your analytics. Do not miss this stage.

What type of data is actionable?

Timely data is actionable.
Data needs to be up-to-date, or else shifting context will erode the ability to gain accurate insights, and it will prevent you from being able to take successful action. Trends change quickly, and a delay in your data could result in a completely missed opportunity.

Comprehensible data is actionable. 
Data needs to be easy to consume. Accessing the data should be easy–it should be presented to the right people, catered to a specific audience, and easy to understand. High-level metrics and KPIs should be highlighted. Embrace modern dashboarding and Business Intelligence (BI) software to provide the best possible user experience. Make the data work for you.

Tip: Dashboards don’t build themselves. Your data analysts/specialists/scientists must play a role in crafting dashboards that follow sound reporting and statistical principles. Rarely do “default dashboards” highlight the data that matters to your business and present it in a way that is most accurately perceived by a variety of audiences.

Accurate data is actionable.
Data needs to be accurate to support good decision-making. The data going into your systems needs to be good. Reducing and removing human interaction and manual data entry is key. Developing high-quality system integrations is key–data flowing from one system to another should be handled with care.

How do you make your analytics actionable?

1. Can you accomplish all of the above internally? If not, get a partner. Effective use of actionable analytics requires a strong data infrastructure and expertise in data analysis. If you lack these resources, you may need to invest in building your data capabilities, or partner with external experts who can ensure you get the most out of your data. Firms with experience developing analytics plans can help get to your goals as fast as possible to start optimizing immediately.

2. Track and report on data that is actionable! Reporting on unactionable data is a waste of time. If your data is not timely, comprehensive, and accurate, then skip it!

   Ask yourself: If ____ metric were to significantly change, would we take any action?
   Work backwards: We would change ____ if we knew ____.

3. Determine who is responsible for insights. Valuable insights come from two types of people: those who have seen the past, and those who will see the future. You need insights coming from people with experience and lessons learned, combined with insights from people who are thinking about tomorrow and trying to predict future behaviors.

   Determine the frequency of insights. You can refine this over time, but it’s a good idea to set a schedule for when to check in on your reporting and “harvest your crop”.

   Incorporate industry benchmarks. Comparing your metrics to peers and competitors can bolster your data with valuable context and legitimacy.

   Use Year-over-Year (YoY) reporting to provide context around timing, expectations, and external factors. This is how you can build your own benchmarks and start measuring performance relative to your own data.

4. Determine who is responsible for recommending actions, and who is responsible for executing those actions.

   Take trackable actions. One action at a time, and match the cadence of your insight frequency. Make note of all action dates in your reporting so that you can clearly measure results and accurately attribute insights to actions.

If you focus your data and analytics efforts on the action you will take, you can untap new potential for your business. If you need help, you can give us a call anytime.