StellarAlgo Partners with NBA to Drive Innovation in Team Fan Engagement. Learn more
For Performance Marketing Teams
Understand and activate your entire fan universe in one customer data platform.
Lead Scoring & Segmentation
Identify and segment fans most likely to purchase.
For Data Teams
Bring disconnected data sources together in the StellarAlgo Data Lakehouse.
150+ integrations unlock fan data from multiple sources and destinations.
For Corporate Partnerships
Discover new opportunities to drive value from partnerships.
Media and Gaming
LA Galaxy drive more than $532k in raw revenue
We built the world’s largest fan database to help properties and partners succeed.
Our team thrives on challenges
Get the latest updates
Meet our team of sports and
Join our team of all-stars.
Aug 17, 2020
The role of a Chief Product Officer is the creation of products that deliver value to both customers and the business. This means that a CPO needs to be really driven to understand their customers and is motivated to dig into their challenges and objectives. At StellarAlgo, our Chief Product Officer, Joseph King, uses his years of consumer behavior and psychology experience, coupled with over 25 years of product development knowledge to help our clients continue progressing on their data-driven journey. He also takes learnings from our customers to find ways to improve our Customer Data Platform features that will help them better use data to understand their fans.
Through his in-depth informational sessions with both our customers and other organizations in the industry, the topic about how brand studies fit into an organization’s single customer view continues to arise. This question generally stems from the challenge teams have to find better ways to use data, including findings from brand studies, for marketing purposes. Although there’s no shortage of data, knowing how to use it, which data points are most important and connecting the dots when data is siloed is hard. In this Q&A, Joseph shares some of his insights and suggestions for how teams can approach these types of projects and why digging into your data first will result in more effective brand studies.
Could you start by telling us a bit about how organizations can leverage their data to inform different marketing strategies?
I see many organizations working hard to leverage data in making decisions, including results from brand studies, but sometimes those brand studies only add to the decision-making challenge. That’s why I recommend teams start with looking at the data they already have and then start to form a hypothesis or to identify an opportunity. From there I always find that it comes down to what your priorities, goals and strategy are to hit specific goals. Data is really important in informing both your priorities and goals as well as what opportunities exist to achieve those goals.
For example, say your goal is acquisition and engagement of new fan segments. A strategy around acquisition would start to put some shape to assessing what new segments are, how big they potentially are, how much they would likely spend, how many of them actually engage today, and how to test engaging and nurturing them to higher levels (i.e. channels). One team we work with took this approach and looked at their region’s overall demographics. They noted how underrepresented their business is in certain demographic groups that have exploded in the area in the past ten years. Based on exposing this data and knowledge, they realized that they had an opportunity to grow in that area. It led to a direct organizational objective which all departments were able to rally around.
How would a team use the data above and apply it to a brand study?
In my experience, getting good enough answers to questions like what new segments could be or how big they are is important because it acts as a good gut check on how much juice is in the squeeze. A brand study will tell you how many pockets of opportunity there are but won’t always be able to tell you if these opportunities are valuable. Brand studies also assume there is a baseline understanding of what your current segments are, how much they are worth, how big those current segments are, the potential size of new segments, and the engagement rate of both the new and old segments. So in reality, there’s a deliberate sequence to these projects.
So what you’re saying is that teams need to dig into their data first to understand segments, and then apply that knowledge to developing their brand studies?
Yes, I mentioned this earlier but so many organizations struggle to leverage data in making decisions and brand studies only add to that challenge. Since brand studies are usually derived from surveys, you can’t always take that data at face value without some further analysis; it’s been researched that a common challenge with surveys is that respondents tend to answer aspirationally rather than how they actually behave. Without that base understanding of who your fans are and how they’re behaving, brand studies can end up being too general and only contribute to the noise that marketers are inundated with. For brand studies to be successful, it is really helpful if they connect to a hypothesis coming from your data.
Let’s say a team has looked into their data and come up with a few hypotheses. How would they incorporate that into a brand study?
Developing a brand study that surveys both internally and externally – in other words package buyers, single game buyers or even non-buyers in your market – can help put some shape and color to specific segments teams feel they’re already engaging with. This is an important tool to start with. A well designed team brand study will also be good at teasing out some actual behavioural answers from aspirational answers (i.e. what people actually do versus what they say they do). However, the best data you have on actual behaviours is your first party data – your sales and engagement data. Brand studies are really good at adding colour to fan data since they’re also better at getting motivational and interest data that is hard to come by. When you combine that motivational and interest data from a brand study with your first party data you can get some really great insight.
When you advise teams on what to do with brand studies, what’s your approach?
I always like to start by asking them some questions because it will really influence how to execute their brand study. Not having a specific goal or reason for doing something like this will end up delivering less value than it could have and at worst is a report that just collects dust on a shelf. The questions I ask specifically are:
Brand studies help teams initially understand who can help them achieve those goals and is a good first step. When combined with first party data you can then start to adjust and narrow down your key segments, how they buy, how they spend and, critically, engage & activate them because you know exactly who they are.
What final advice would you give to a team considering developing a brand study?
I would say there is always an opportunity to get even more out of the data in your database to identify your best fan segments, their value, and how they engage. I would also suggest that starting with those segments from your database in conjunction with a brand study can provide a really valuable baseline especially on the value and engagement of those segments. Additionally, I would stress that whatever survey data the brand study acquires finds its way into your database and is attached to those segments, or customer profiles, so you can leverage it in propensity modelling. Finally, I like to remind our customers that the data you pull from your database and the data that is captured from your brand study will also give you a clear line of sight into activating those segments and measuring your improvements/progress towards your goals.