Analytics vs. Insights

Episode 11 September 13, 2022 00:18:46
Analytics vs. Insights
The Loop Marketing Podcast
Analytics vs. Insights

Sep 13 2022 | 00:18:46


Hosted By

Elise Stieferman

Show Notes

In this episode, Coegi's Director of Data & Technology, Jake Amann and Radar Analytics President, Candice Rotter, join us to discuss how to find the meaningful insights in your data analytics to move your brand closer to it's business goals.  


What You'll Learn:

-The difference between analytics and insights

-How to visualize and find insights in large data sets

-Ways to communicate results business results using dashboards

-How to plan and set up analytics before a campaign starts

-Data storytelling tips and ways to incorporate non-media data insights


Analytics is using data to do something - the what. A standardized, repeatable process. 

Insights are actionable nuggets pulled from analytics - the why. The meaning behind your data. 


Any time you are working with data, you must start with detailed planning. 


What's the goal of the campaign? 


What do you want to learn? 


Then, establish proper naming conventions, understand data requirements and have a proper measurement plan before you start any campaign. 


If your business objectives and campaign objectives are clearly understood upfront, you will be able to quickly see the story in the data and understand how advertising is impacting your business goals. 


The role of data analysts is to use data to improve the next campaign. Listen to learn how to communicate results to the boardroom as well as to the marketing team. 



0:00-0:27 Intro

0:28-2:44 Defining Analytics vs Insights

2:45-7:13 Visualizing Large Data Sets

7:13-9:01 Communicating Insights w/ Dashboards 

9:02 -12:15 Showing Impact on OKRs

12:16-13:21 Communicating Good and Bad 

13:22-14:34 Have a Single Source of Truth

14:35-17:01 Data Storytelling 

17:02-18:08  Analyzing Non-Media Data 

18:09-18:46 Outro


View Full Transcript

Episode Transcript

Elise: Hello, and welcome to the loop marketing podcast. I'm your host Elise Stieferman, Director of Marketing at Coegi. Let's get started. All right, today we are here to talk about analytics and insights, and I am joined by Candice, President of Radar Analytics, as well as Jake, who is our Director of Data and Technology at Coegi. So thanks for joining me today, guys. Jake: Good to be here. Candice: Thanks for having us. Elise: Okay, so let's start with the basics of analytics versus insights. So we know the two are very closely related, but have very different implications. So, Candice, I was wondering if you could kick us off by talking about what truly is analytics? What are insights? And what should marketers know about the two? Candice: Yes, so analytics is really about using the data you have to do “something.” That “something” could be just understanding the environment that you're in today, that “something” could be predicting the future and what it holds. It could be improving on a process, or performance, or whatever we're really trying to achieve by this collection of data. Where at the end of the day, the insights are something that you can act upon. It's a nugget that we find within all of that data that you can act upon and move forward with. So there's really no purpose in combining all of this data if there isn't anything you can do with it, which is really what the end goal is. Elise: Right, so the analytics are basically the what, whereas the insights are the why. Jake: Yeah, and really analytics is somewhat of a process. It's the way we approach a problem that is standardized and repeatable. So we're doing the analysis today, but when we want to do it again in three months we can see, did things change between the two time periods. It's really just kind of how are we going to go about answering this problem and really at the end of the day, our clients, at least for Coegi, are after a lot of those insights. So a lot of people clicked on my ad. What does it mean? How are we taking this a step deeper? How are we changing our campaigns based on that so we apply an analytical approach to get to those insights for our clients. Candice: But you can't really find an insight unless you know what you're looking for, or if there's a purpose behind it. I think that's where it comes up to really understanding the goal of the collection of your data at all, before you can really get into your next step. Elise: Right, and so it really just starts off with your measurement strategy, and wanting to understand what you're going to learn about, what you're going to test, things like that. You know, just thinking about the world of digital marketing in general, we are empowered because there is a ton of data available for us, but it also can be completely overwhelming to figure out which pieces of data are more important to actually inform business changes, things like that. So, Jake talk to me about how you make sense of large data sets, and how do you either use visualizations or something else to draw out key insights? Jake: Yeah, that's a great question. It really starts in the planning phases and I'm not just saying that. If you don't have a hypothesis or something that you're wanting to test, when we run this media plan, are we getting more awareness for our client? We can talk about how you measure that at a different time, but you know, you have to have that mindset. Then when you do that, you need to know, these are the cuts of data that we need to report out on that. So you need to know your data requirements before the campaign even goes live. If you're trying to figure them out or add them mid-flight, you might even have to throw out the first couple months of data. You can't make cuts of data. If you launch a campaign without a relationship between campaign name and adset and creative and your platform and your budget spreadsheets and all these other documents, if there's not a relationship up front, you can't add it in after the fact. So it starts with good planning. When we're talking with really big data sets, there's a couple different problems you can run into. So sometimes it's how fast the data's coming in. So we don't necessarily have that problem. It's once a day, it's not microsecond like financial trading, although some of the ad decisioning is done on a microsecond scale. When we're talking about the data we need to make the decisions of how do we target our campaigns. It's more of a daily schedule, you know, it's hundreds of gigabytes a year, but it's not petabyte scale. A lot of it's about the variety or the inconsistencies. So I work with Candice's team a lot on mapping tables and fixing the problems, and go back and kind of put a bandaid on some of those problems. So if you can fix a lot of that upfront, you can feed the data into a machine in a much more clean manner. So that's a lot of it, it's having a plan, executing it, knowing your data requirements and executing against it. So, that does mean you can't scope creep, you know, we're halfway on the project and we want to do more. Well, you can't do that, and that's a hard conversation sometimes for our client services teams, but you have to be up front. So it's a lot of open, honest conversations about what you actually want. You know, if I spend a thousand bucks, I can't drive more than a thousand purchases, with under a dollar CPA, it's just not happening. So, having an actual goal you can expect from a campaign of this size and these markets, targeting these audiences. It's about good planning. Candice: Yeah, I think the other part is in creating a visualization that is easy to understand, right? So really our goal is on every view we create within five seconds, you should know the answer to what that goal or what that view is trying to tell. So we do a lot of indicators, red, green, yellow, you know, are we on pace or are we not? You shouldn't have to spend a lot of time to find out if what I'm doing is working or if it's achieving what we set forth. So that really is our goal is if you have a ton of data, the first thing you have to do is really put a wire frame out. Here's what we wanna tell in each view. Here's what the question is we're trying to answer in each view and then bringing it all to life. So that quickly within that five seconds, you know, what is you're supposed to? What is that forefront of that visualization with as much data? It can be very overwhelming. The last thing we want is for people to be overwhelmed and not use their data. That is a waste of time for everybody. We talk about naming conventions, all this mapping, everything we do to get it to a spot where you can actually use it. So we want it to be easy, to understand and fast, which is not easy, but it's something that we all love to do. Elise: And It varies a lot by stakeholder, right? And the savviness of data analysis. I mean, it's a lot of storytelling based off of who your end user is. So can you talk to me a little bit about how do you put together visualizations for the day to day marketer to be able to draw out those insights, versus maybe someone like the executive of a company who basically wants to know, how's it going and wants a quick answer? Candice: Yeah, the way we approach it is the first few views of a dashboard are going to be very high level. So the first one is always the executive view. It's those core business metrics that we've talked about before we even started working with them, where we started any campaigns of what's important to them so that they can get in and quickly export it out. And here's my recap, here's how we're doing, here's how much we're spending, this is where we're spending it at. Then we get into the next few, which is going to be your media snapshot. Here's what's going on, here's the audience we're talking to, here's how many people we're reaching, here's how many new people we're reaching, and then it'll get more granular as you go. So that if you don't want that information, or you don't need that information for your day to day, you don't have to look at it. But those next views are gonna be much more granular: is the creative working? Which creative component is working the best? How are they entering the funnel? What channel are they using to enter the funnel compared to what channel are they ultimately converting on? What is our customer segmentation doing? Are we growing in those? Once we start targeting new home buyers, are we making an impact or are we not? So all of those are going to get more in the weeds, more for optimization, more for the day to day, the marketing team, but the executive views are gonna be very high level. So at a glance, they know we are doing the best we can with their dollars, and it's going the way that it's supposed to. Elise: So with that, thinking about executives, they're oftentimes asking pretty lofty questions, like the age old “is my advertising campaign working?” Pretty substantial question there, so how do you take the data and truly tell a story with it about the impact of advertising. Candice: Yeah, I mean, the most important part is identifying what is success up front. A lot of times why people do not use data is because that's never defined. So when you start to dig, it seems like an endless hole and you don't know what you're searching for, but if there is a strong measurement strategy and we understand the overall business goal, and we understand each channel's objectives, it's very easy to say, “is it doing what it's supposed to or not?” Without that, that's when it becomes complicated. So my advice is always to spend more time upfront talking that through, talking through the strategy from a media perspective, but also a business perspective and create a data strategy as a whole, before you even get to the part of talking about visualization or talking about what we wanna do in terms of analytics. Then it will all come into play and be very easy. The amount of time you spend should be way more upfront than it is actually building out that product. Jake: I think it's also important that you don't just kind of backfit your expectations of the campaign based on what happened, because you always need to go out there and say, “I think that this campaign is going to drive people to consider purchasing our brand the next time they're at the store.” Well, what if you're trying to drive this brick and mortar strategy and your e-commerce strategy is exploding. You don't just say that this was a perfect e-commerce strategy. You need to break down what it is about the audience that we are targeting? Did they go in different directions, so your clients should know what your goal is before. Everyone should be in the know, and if things pivot, that could be a good thing, could be a bad thing. If it is a good thing, you have to explain, this is good, but it's not necessarily what we wanted to do. This is why it worked, and also inevitably, if it doesn't work, you can say this is what we set out to do, and we missed it by 15%, but, this is how we're going to change our next plan. Like we're going to cut these tactics or these channels completely from our next plan. If you just kind of figure out your measurement strategy halfway through the campaign, or, you know, after it launched, you can revise it though. These things are living documents. We do change our plans, but you should go in with a plan to test something. And if it doesn't go to plan, you know, evaluate why, report that back out and that's gonna help you get some insight to your client. You're gonna really, you know, hopefully be able to get some really useful insights, what worked, what didn't work. That's what our clients really want to hear. You know, how do we change our 2023 plan based on 2022 results? That's the type of questions our clients expect us to be able to answer. Candice: Well, and I think it's important what Jake said about not everything is going to go perfectly, right? And you can't be afraid of that. You can't cover up bad data, right? That data is there to also help move you forward, and your clients will respect you having that conversation of saying, “Hey, this didn't go as planned, but here is our next step and this is what we're going to do and try this out.” It should always evolve, but ignoring it or expecting every campaign to go perfectly from the beginning is unrealistic, and you're gonna create stronger stickier relationships if you have those types of conversations and use the data for both the good and the bad. Elise: Right, I think it's really important to have those transparent conversations and build that trust, and that all starts off with having alignment. Understanding what I should be looking for and the insights are, okay, this is the direction it's going, why? So, is it the audience? Is it the channel? Is it the creative? Being able to drill in further and figure out what needs to shift to get them closer to their business goals. Jake: I think something that Cogi does is we're calling them different things, I think they're currently called a client charter, but just one document that's got everything. It's literally a resource, you know, a reference guide. So everyone has a single place, a single source of truth. We all know what's going on, what's happening, and it's synced up with a lot of our other internal systems to make sure that this is a one stop shop for a lot of people to go get the things they need, whether that's planning or it's reporting. So, I think sometimes people think of planning and reporting as two separate things, rather than a continuous cycle that is full circle, which a lot of people don't always think about the end and I think Candice and I would both argue you should start with your report first. The outcome, what are we trying to prove? How do you build the media plan to get to that? So, I think it is important that you know these things up front prior to the start. Have a great plan and then measure if it worked or not. Elise: So obviously measurement is very important to us. How do we go and look beyond just performance alone and really use data to tell the business story, to be able to gain new learnings about who the customer is that was maybe previously veiled, or what value the customer sees in a certain product. So, how do you go beyond just, “this is what the media did”, and tell the story. Jake: And I think this goes all the way back to what Candice opened us up with, when you're being analytical, you're looking at everything kind of, can I make this better? Is this optimal, because really what we're going to get to is doing things better and faster, kind of at the same time. Both better and faster at the same time, that's why we implement these solutions, because they're repeatable. They can do the same thing over and over. If you find yourself asking the same question over and over, build a solution that's going to answer that question over and over and not need a lot of human intervention. So, a lot of this is just moving faster as a company because our clients are asking us more questions, different questions. Sometimes you wish it was cookie cutter: I can just do this report, then I can do this report, but that's not the reality of what our clients need. You know we don't represent one niche. We're not a one vertical company where we just do agriculture really well or healthcare really well. We have to do everything with a lot of different stakeholders. I think a lot of that goes back to multiple views and reporting and making sure that every stakeholders gets their own view. Everyone needs a different piece of information, but what's great is it all somewhat boils down to 15 columns of data. We do have a ton of data, but the one that I need for this report is only this set of data. That's gonna be there every day for me, and the data flows to that report. It's prepared in a nice, consistent, repeatable fashion, and then based on that, we do something. So that's the setup and how it ultimately hopefully flows. Candice: I think the other part of looking outside of just performance is thinking outside of the box. I mean, the nice thing about the world that we're in right now is it's so different every day, right? There's something new that we can bring to the table that's never been done before, which makes it so fun, and at the same time you can use all this outside data that has nothing to do with media, but will help you to understand digital popularity or understand how people are engaging with your brand or what is their sentiment. That's not just performance, but how do they feel about you? Those are all just as important than getting that last conversion, but it also gives you the chance to have fun and come up with something new and unique that you haven't had the chance to do before. So we really strive to do that where not only are we looking at media, but how can we tell them more about their consumer? How can we tell them more about how each market looks different and how they need to communicate to them differently based off of what we're seeing in other places? So, the nice thing about this is it's fun, and we get to do a lot of new things, but it helps them use that data and not be intimidated by it at the same time. Elise: Great. Well, thank you both for being here. It was a great conversation. We look forward to seeing you next time. Elise: Thank you for listening. Coegi is an industry leading performance marketing agency based in the Midwest. We've learned a lot since our founding in 2014 and started the loop marketing podcast to share some of our hot takes on marketing trends we're following, best practices we've discovered, and actionable tips for improving your digital strategy. We'll see you next time.

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