Agile Marketing Based on Analytical Data Insights: Improving Scrum Tactics in Brand Outreach

This post is written by Mathias Lanni (Executive VP, Marketing – Velocidi).

Agile management and scrum-style techniques have long been accepted in fields of technology development, but have been increasingly adopted outside the tech industry over the years.  Fundamentally, agile tactics are a way for organizations to more quickly adapt to quickly-changing markets and customer demands, without the slow-to-change hidebound nature of top-down hierarchical organizations impeding change.

Marketing has certainly become fast-changing!   The marketing field has become extremely volatile in the past 10-20 years, with the digital revolution bringing about huge changes in buyer behavior, brand/buyer interactions, as well as basic outreach.

Agencies were already having to deal with client demands which could change rapidly based on customer demands and/or issues with their image.  Now, on top of that, digital marketing is constantly in flux, with massive shifts in strategy consistently happening in response to changes in the search engines as well as the impossible pace of internet/electronic trends.  It’s enough to drive any marketer to reassess their workflow, which is undoubtedly why agile techniques are coming into the field.  The issue is how to introduce scrum-style strategies while also making use of “Big Data” analytics to ensure the best possible decisions are made.

In this blog, we wanted to address a few ways data analytics can be integrated into scrum-style workflows in a marketing management setting, and in particular how they can be utilized to quickly settle questions that may come up due to shifting priorities.

Improved Scrum Marketing Management through Smart Use of Data

We’ll assume readers are familiar with the basics of scrum management.  Rather than go over that, we wanted to address a few specific problem areas relating to Product Owners and Scrum Masters where data analysis can be of the greatest help.

Problem 1 – Sorting Through the Backlog

One of the perennial issues with digital marketing is that there is always more that could possibly be done than even the biggest team could ever achieve.  As an easy example, there are literally dozens of social media networks out there.  Yet even the largest of brands is going to struggle to support more than a handful properly.

So when you have a long backlog of user stories to implement, how do you prioritize?

This is exactly the sort of problem a well-maintained database and analytical system can cut through easily.  By sorting through usage data, customer feedback, focus group comments, and similar information, one can almost always get clear guidance on which user stories would likely be well-received by the target audience(s).  With sufficient data, there is no need for guesswork – you’ll have clear trends indicating the right path.

Of course, this principle also applies to selecting user stories in the first place.  A data-driven outlook will help ensure effective stories are selected, leading to a backlog full of to-do items which all have a high likelihood of paying off.

Problem 2 – Optimizing Your Points and Time Allocation

Historically, one of the biggest issues facing Scrum Masters is properly configuring your sprints.  How many points should be in the sprint, and what time allocation is best?

Don’t forget that big data can be applied to your own processes as well!  A database keeping track of the successes and failures of your own scrums will serve you well, and generally, it only requires a few months’ of data before you can start seeing clear trends.  Allocating points doesn’t have to be a matter of gut and instinct.  You’ll be able to look up exact time spent on similar user stories in the past when determining your time allocations, which in turn gives you clear guidance on point’s allocation.

Of course, this does rely on committing to recording these numbers and doing so consistently.  This small time investment will pay off in the future – and do so with increasing reliability as the months’ pass.

Problem 3 – Crafting Effective Retrospectives

It’s well known that human memory is quite fallible, particularly when under stress.  This can be a problem when it comes time for your monthly retrospective.  How well will people really remember the nitty-gritty of problems faced in the previous month?

Again, this is a problem which can be solved with good data and time tracking throughout the scrum process.  The Scrum Master might even devote some time to reviewing the data logs.  Why did a particular Team Member end up spending twice as much time implementing a User Story than was originally allocated?

They might not remember this event off the top of their head without prompting, but with the data on the table, it’ll be much easier to remember.  Then the information about the problem and its solution can be integrated into the database, and into future decision-making.

Data Can Tie Your Marketing Together

These are just a few examples of how data analytical techniques and scrum-based marketing management can go hand-in-hand.  Data can be the basis for decisions throughout the process and will make the lives of both the Product Owner and the Scrum Master vastly easier.  In most cases, a trip to the database will be able to answer most pressing questions – clearing the roadblock quickly – while the ever-increasing amount of data recorded will help you quickly optimize your scrum processes on a month-by-month basis.

About Mathias Lanni EVP, Marketing – Velocidi

Mathias Lanni has helped some of the world’s leading brands take advantage of new emerging technologies to reach and engage their audiences. Through 20+ years of brand marketing experience Mathias has helped large national advertisers incorporate paid search, display advertising, conversation analytics, social media marketing, social advertising, web & app development into their traditional marketing plans. Before Velocidi, Mathias was a founding member of Edelman Digital, the world’s first global social media agency, where he led global scaling plans for the agency. Mathias currently works with 

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About Eric D. Brown, D.Sc.

Eric D. Brown, D.Sc. is a data scientist, technology consultant and entrepreneur with an interest in using data and technology to solve problems. When not building cool things, Eric can be found outside with his camera(s) taking photographs of landscapes, nature and wildlife.
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