Marketing Leadership Conversations
is a virtual series designed to extend your learning and the effectiveness of your organization as it continues to transform. This episode features Margaret Wise, CRO at Arke and host joined by Marketing Leaders from Insurance, SaaS, Professional Services, and Manufacturing organizations.
Transcript is edited for clarity and length.
Margaret: Thank you for joining me today for our small group discussion about data. We are going to talk about how far we’ve come from small, corporate databases to data lakes, what makes data important, how to leverage your data for personas and how to analyze your data for customer acquisition and retention.
One of the biggest challenges when it comes to data is figuring out what is important and what isn’t. There are a few criteria that help us identify important data:
- Data that is reliable
- Data that is accessible
- Data that is relevant to your KPIs
- Data that is actionable
The best place to start clearing out the noise is to conduct a data audit with a ‘MarTech Stackie‘. If you’re not familiar with the term, it is a visualization of the different systems that are collecting data related to your customer experience. There are varying levels of maturity.
Do you see your MarTech Stack as simple, intermediate, complex or somewhere in between and why?
Marketing Exec at Professional Services Company: We are a small company with minimal sources to leverage our internal data, so I would consider us to be simple.
Marketing Exec at Manufacturing Company: We’re simple also. We are at the beginning stages, just trying to really understand and implement what will give us the best insights.
Margaret: I would say ours is probably intermediate and I think that’s because of the number of platforms that we have and the amount of data we’re sharing across platforms. We’ve simplified ours a bit in the last year and put in a new marketing automation system that gave us better insights and more closed loop analytics around our marketing.
Interested is developing your own ‘MarTech Stackie’? Leverage our Marketing Strategy Workbook. Measure your organizations marketing maturity and gain insight on what strategies to focus on next.
The next topic I’d like to talk about is if the data you have informs personas? If so, what parts of the data or how do you use the data to help identify those personas?
Marketing Exec at SaaS Company: I learned a lot about this from prior experience with another company. We were told who our target audience was, who we were working with, etc. with no real explanation. When I started digging into the data, we were able to figure out that what the organization thought was our focus for our clientele was not even close. Then we dug deeper to truly understand who came to our company and who the decision-makers are for different product lines.
Margaret: Very interesting. I’d love to ask our participant in the Insurance industry – how are you thinking about customer insights and breaking those down into audiences or personas? Have those personas been given to you or are you trying to dig into the data and figure out what they are?
Marketing Exec at Insurance Company: A mix of both. Every 2 – 3 years we try and do focus groups to understand what people are looking for and really what’s driving them to order from a national carrier rather than the regional carrier.
But, I’m more focused on looking at the data from a risk perspective and understanding from our current customer base the types of policies and businesses that are the most profitable. I’m digging into the data in the claims and understanding what types of vehicles, drivers and people are on the policies that are the most retaining, most profitable, etc.
Margaret: Interesting and you touched on a few of the next topics. Behaviors and intent. You probably have a lot of information around what the behaviors are of your customers. Does that help you figure out what customer you should be targeting?
Marketing Exec at Insurance Company: Correct. We track a lot around the geography and demography of our customer base. Through census data and insurance scored data we can see affinity groups that we can go after and target from social and marketing perspectives.
We also sit down as a group and look at the behaviors leading up to the purchase decision. For example, if someone is buying a car, they’re going to need insurance, so we try to marry that car buying journey for the customer and see what the behaviors are leading up to, during and after the purchase.
Margaret: That’s really good. It seems like once someone gets closer and closer to purchase you have a lot of data to work from there.
The next topic is a bit newer, around the idea of intent. There’s a great deal of intent data available to us that help us understand what people are searching for or what their buying intent might be.
For example, in the insurance industry, we had the VP of Innovation at USAA speak at one of our events about how their team was thinking about intent, customer experience insights, behaviors, etc. The example he gave was that if someone opens up the USAA mobile app at 11pm in a location that is not their home location, then you had a pretty good indication that an accident happened and their intent was to file a new claim. To make the experience personalized, the app would open with a prompt of ‘Do you need to file a claim?’.
Are you thinking about how data can help indicate explicit and implicit behaviors and how we can extrapolate that to provide a more personalized experience?
Marketing Exec at SaaS Company: When I was working for an agency, we were importing intent data from Bombora to then personalize the experience on the site based off some characteristics they were utilizing from the database. We were able to pull content forward quickly that they were interested in. Not in a way that it was right in their face, but in a way that was more on the side panels.
Margaret: It’s good to note that intent happens over time and it’s important to leverage it throughout the various stages of the journey.
The last question I want to put out there is kind of the holy grail for marketers. How are you using the data to help you forecast? In a utopia world with unlimited budget and resources, what kind of data would you want to achieve acquisition and retention?
Marketing Exec at SaaS Company: I’ll jump in on this. Since the global pandemic, we’re seeing 8x as much content being created in our platform on Sundays compared to a Sunday prior to the virus. What made me dive a little bit further and think is how can we extrapolate moving forward if we see a dip, whether there are issues with our clients using the platform and if that will lead to churn or not. It’s a great data point that sometimes we don’t look at but could mitigate churn.
Margaret: That’s great insight. Anyone else?
Marketing Exec at Insurance Company: I want to chime in, and I would say that probably our worst use of data is to forecast. It’s hard for us from a customer segmentation perspective to understand the person that doesn’t want to be talked to and doesn’t really want to be interacted with to the person that wants to have their hand held through the journey. I’m working to identify those from a churn and acquisition perspective. In terms of churn, it’s understanding what content we need to push to who. For acquisition, it’s understanding what’s resonating with people and ensuring that we continue to push that out while constantly monitoring and evolving our marketing pieces.
Margaret: I’d imagine insurance would be tough because the goal is no claims or engagement, right?
Marketing Exec at Insurance Company: Correct, but there’s a lot of variety and scope of our customer base. There’s someone who doesn’t want to be talked to and does everything digitally, but then others that want to be in the insurance agency office paying in cash. So, you must marry the in-person and online journeys of where someone called in or came in to meet with an agent vs a fully digital journey that we’re trying to get to.
Margaret: When you’re thinking about acquisition or retention, do you have offers that get promoted out to existing customers vs. those that are primarily geared toward customer acquisition or have ways to measure engagement around that?
Marketing Exec at Insurance Company: Yes, we have both. We have an agent software that the agents will push content out of and contact certain customers for different product offerings. It’s more focused around acquisition – that’s the show.
Margaret: One last thing when thinking about that. Content strategy was mentioned earlier – do you have content strategies that are geared toward existing customers at all and do you have ways to measure if there’s engagement in that?
Marketing Exec at Insurance Company: Yes, absolutely. It’s still in the beginning stages, really starting to get our email campaigns to existing customers ironed out and using those marketing analytics to understand if people are converting into new product offerings or increasing coverages, etc. It’s definitely on our roadmap.
Margaret: It sounds like you’re on the right track. We work with a lot of different companies and for better or for worse, it’s always good to know that nobody has all their data figured out. Nobody has a sophisticated MarTech stack. Nobody is leveraging their data perfectly to get the best insights and predictive analytics in place. So regardless of where you are in your data journey, you’re not alone. Thank you all for sharing your perspective on data today.
To recap, here are a few of the key insights shared today:
- Cut out the noise by determining the data that’s important with four criteria: reliability, accessibility, relevancy and actionable
- Start with a MarTech Stackie to determine all the systems that hold data relevant to your customer experiences
- Leverage your data to truly understand your personas and audiences
- Think about how your data indicates intent that can guide a more personalized experience
- Measure your marketing and content effectiveness to improve acquisition and retention
I’d love to connect and brainstorm how you can make data-driven decisions for your organization. Contact us to schedule some time to chat or go straight to our calendar and book a spot. email@example.com | www.calendly.com/arke-1/