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What is Agile analytics?

February 1, 2019

 

1.Context and challenge

 

In a digital world which is continuously evolving , the ability to deliver timely solutions is vital for any agency. The traditional “waterfall” methodology, which is non-iterative and suited to projects where business and requirements are fixed and clearly understood, seems to create more barriers than supporting teams for coping with clients’ unpredictability. Project management becomes more challenging and unique than ever for digital analytics teams because client’s requirements and updates seem never reach an end state, although every phase of a project has a start date and an end date.


Among numerous methodologies that a project manager can choose, agile has been considered as an appropriate approach for digital analytics project, to adapt rapidly and cost efficiently in response to unpredictable changes. In other words, agile is the ability to move quickly and easily in all circumstances. In the digital marketing and digital analytics fields, it means using data and analytics to continuously create value for customers, deliver super timely solutions to problems in real time, deploying tests quickly, evaluating the results, and rapidly iterating.

 

2.History and definition of agility

 

Back to 2001, the term “Agile software development” was coined by a small group of software industry leaders to describe a methodology based on iterative development. Any software method is considered agile as long as it adheres to the four principles of the Agile Manifesto, which values:

  • Individuals and interactions over processes and tools,

  • Working software over comprehensive documentation,

  • Customer collaboration over contract negotiation,

  • Responding to change over following a plan

Agile has succeeded far more from the software industry and was adopted in other industries as well, either by large and traditional companies or small start-ups.

 

3.Tips for being agile

 

Step 1: Collect data since the very beginning of the project

Set up data tracking and start collecting data as soon as possible. The small set of data collected can be used as a sample to test the tool configuration, the tagging plan and the goals. As long as an abnormal event is identified, a corrective action can be quickly planned and deployed. You don’t need to be 100% sure before you make decisions. Even if you fail, you fail fast and you fail cheap.

 

Step 2: Visualize data

Human brains cannot digest thousands of rows of reports, but can easily understand huge amounts of complex data in the form of visuals. Visualization allows audiences to recognize patterns quickly to make appropriate and timely decisions. It can also help identify areas that need attention or improvement, clarify influencing factors, predict how the business result will be if no action is taken, etc.

 

Step 3: Analyze data

Data visualization is not enough. To cope with the volatility created by customers, react in real time and make the customer feel personally valued, advanced analytics is the only possible solution. Data analytics provides insights to understand customers’ need, anticipate market demand and deliver great experiences.

 

Step 4: Collect feedback and react

Continuously communicate the analysis results to the relevant actors and collect their feedback to act in a timely manner. This process should be done on a weekly or even daily basis. Any updates and changes can be resolved in the next iteration. Remember to maintain a database of all the changes that significantly affect data, in case you need to revert back or compare.

 

Step 5: Collect more data

Scale up your database to enrich reports and analysis. Once you gain insights from the current datasets, you can add up with more data sources and combine information from different sources to your reports. It helps reveal hidden and sometimes, key influencing factors that usually a single data source can’t show.


And the loop continue until the end of the project with all updates implemented. Do not conform to any particular process, take any path to solve the found problems. The whole point is to move quickly and easily.

 

4.Conclusion

 

Data analytics is the topic in which companies  invest to drive business productivity. And the bad news? Analytics is a difficult transformation to struggle with. As a risk, lot of money might get poured into unproductive holes.

 

It’s very much about re-thinking the way the organization is setup so that analytics is embedded and operationalized. It’s even more about finding ways to re-tool our thinking so that agile concepts and controlled experimentation are everywhere. A clear vision and a small team of talented people with skills across multiple functions who can work together at speed might not guarantee success, but surely contribute as indispensable steps on the stair to the top of productivity.

 

For further info, you can meet us, call us, message us or take a look at our website www.drive-agency.com

 

Talk to you soon!

 

About DRIVE

 

Created in 2017, DRIVE is a digital performance company providing clients with a data-driven marketing strategy, powered by skilled talents, reliable data and scalable technology system. Certified on major analytics and conversion solutions such as Google Analytics, AT Internet and Adobe Analytics, we combine our expertise to meet your business expectations. With experience in both brand and agency matters and working within international environments for more than ten years, we can accompany you in facing your challenges.

 

 

 

 

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