Driving omnichannel marketing performance with Ontario Lottery and Gaming Corporation

Key takeaways:

1. Unified data for smarter decision-making

OLG tackled the challenge of managing data from multiple teams and campaigns by creating a centralized media performance hub. This consolidated approach ensures all their data is easily accessible in one place, providing a clear view of what’s working and helping the team make informed, efficient decisions.

2. Scaling successful campaigns

Through detailed data analysis, OLG identified their top-performing platforms and campaigns. They used these insights to scale up what worked best, ensuring their resources were spent on strategies that drive the greatest impact.

3. Automating for efficiency

Manual data collection was slowing the team down. By automating reporting processes, they saved time and reduced errors, enabling their team to focus on strategy and deeper analysis. This shift increased reporting capacity by 75% and cut manual work by 35%.

4. Staying agile with seasonal trends

For OLG, customer behavior often aligns with seasonal events like sports seasons or lottery jackpots. By analyzing historical trends and reacting to real-time data, the team fine-tunes campaigns to match market demands and maximize engagement during key moments.

5. Creative and audience optimization

OLG uses data to test and refine their creatives, ensuring they resonate with the right audience at the right time. This iterative approach improves campaign performance and ensures their messaging aligns with audience preferences.

6. A customer-centric strategy

OLG keeps their customers at the heart of every campaign, using data to better understand their preferences and behavior. By aligning their strategies with customer needs, they enhance satisfaction and deliver more impactful marketing.

Transcript:

Edward Ford:
Hi, I'm Edward from Supermetrics and this is the Marketing Intelligence Show, the podcast that empowers marketing leaders to work better with their data and make sure every marketing dollar counts. Now let's get into today's episode.
Zachary Bricker:
Okay there. Welcome back to the Marketing Intelligence Show. My name is Zach and I'm the lead solutions engineer here at Supermetrics. In today's episode, we're going to hear from GOCO Passant, who's the performance manager at Ontario Lottery and Gaming Corporation, and how they use Supermetrics to analyze omnichannel performance across all the different channels that they use. goco, pleasure to meet you.
Gokul Prasad:
Thanks so much for having me.
Zachary Bricker:
Yeah, absolutely. We're super happy to have you here. Before we jump in to the meat of this episode, goco, just kind of curious how you wound up here working for the Ontario Lottery and Gaming Corporation, and sort of if you could eaxpand a little bit on what your role is there.
Gokul Prasad:
Yep. So I'm the media performance manager here at Ontario Lottery and Gaming Corporation. So in my role I manage media performance and media analytics across various products and multiple line of businesses within OLG. It's my primary responsibility to ensure that our media dollars are spent most efficiently, which is where tools like Looker Studio and Supermetrics plays an important role. These tools majorly help us gather data from multiple silos, providing a consolidated view that allows us for a better decision making, which is really important in such a performance driven company or industry that we work in.
Zachary Bricker:
Yeah, that sounds amazing. As far as your data sources, how you integrate everything. I know we spoke offline previously about how everything coming into one silo was really helpful for you. You have all those disparate sources of bringing everything together. How do you ensure the seamless integration of data from earned owned and paid media channels into Looker Studio? And if you could, what challenges have you encountered in this process?
Gokul Prasad:
So when we started this project, it actually came from a problem we were trying to solve. We have a lot of campaigns in market, there are multiple teams involved and there are a lot of data points that we'll be using to make a decision. So what happened is everybody in the company felt we need a centralized hub for media performance. And that's where we started to think about Looker Studio because we were already using it for some platforms and we felt like probably it's a good tool to actually scale up and use it across multiple data platforms. That's where we actually went into the market, see what are the options we have, and that's when we learned about Supermetrics and how Supermetrics can bring in a lot more media platforms into Luca Studio. And we were really interested. So I would say the entire project almost took a year for us to evaluate and see how Supermetrics can help us.
So right now we use both Supermetrics and Looker Studio to facilitate the integration like Supermetrics, help us pull information from multiple platforms into Looker Studio and provide that consolidated view of our media performance. And like I said, at the core of what we do, we actually feel that all the decisions we take should be actually an informed decision. So the goal is to always make sure that we drive growth business calls and customer satisfaction, and by taking the right decision we'll be able to connect more effectively with our customers through the media channels and improve their gaming experience and satisfaction as well.
Zachary Bricker:
Awesome. Thank you so much for that, that you've got a lot of insight there for the whole process and how you do integrate those sources. I know you said it took about a year to do the evaluation. What was that like? Could you expand a little bit on that? What went into your evaluation of, hey, one, how do we get to the correct tooling and then what goes into the evaluation of that to select that tooling, whichever you're going to use.
Gokul Prasad:
Yep. So when we were actually exploring multiple partners, Supermetrics, one of the key things we looked was actually the number of data points that a partner can bring in for us. And that was one of the key factor where we feel that in today's world there's a lot of data available for everyone, but the problem is that which data we should be looking at. So what we found with Supermetrics is that there's an option to bring in more data points compared to any other platforms out there. And that was something really interesting. And the good thing is that we were able to find almost all the connectors for all the media channels through Supermetrics, which was also really great.
Zachary Bricker:
Incredible. Thank you. Now we're going to switch gears a little bit, and I kind of wanted to dig into that initially in your first answer you were mentioning about the analytics and what helped drive that. Can you share an example of trends or insight you discovered through Looker Studio that led to a strategic shift or innovation in your marketing approach? Or could also be something like how does the marketing team or leadership team use these analytics in their day-to-day? And then how are you aligning strategically with that?
Gokul Prasad:
Yep. At all, G, whatever we do, customer is at the core of everything. So our primary goal is to ensure that we are serving the right creatives to the right audience. And what happened with Supermetrics project is that we were able to identify the key trends and insights from all the platforms in one single dashboard view. And for example, there were some times when we were able to identify whether the right creatives were resonated with the right audience. We also identified what platforms performs the best for us. So there was a lot of things we were able to uncover last year through supermetrics and some of the key initiatives was to actually scale up some of the best performing tactics and campaign to make sure we have the right efficiency across all the media channels.
Zachary Bricker:
Excellent, excellent. And do you leverage any predictive analytics with that? I know you were talking a little bit about how you're scaling things up and what that looks like. Is there a space for prediction in there or are you still sort of couching everything inside of just looking at the historicals and basing it off of that performance there?
Gokul Prasad:
So we have some products that's actually really trending with the market trends. So for example, we have a sports division where the entire business is actually driven across the sports seasonality and we have a lottery products which is actually purely driven by the lottery jackpot amounts. So what happened is we have to make sure that we have the right strategies in place based on these factors. And the best thing to look at is actually the past performance where we see how these audiences reacted to each factors each time. Then we went into the market with multiple testing strategies and the good thing is that all the data is coming back to one platform. We can actually see the trends across all the platforms in one view, which was really crucial. And like I said, we now have dedicated strategy for each trend and we are trying to set that up for multiple trends as we progress as well.
Zachary Bricker:
Great. So it sounds like you're looking at a lot of seasonality there because when we talk about sports seasons, typically there's a lot of seasonality that happens with that. Football happens in the fall, basketball, et cetera. What's one of the most surprising trends that you've identified, if any?
Gokul Prasad:
Like I said, sports season is really competitive. Like Ontario market just opened up a couple of years back. So what happened is we have new competitors in market and for us to stay ahead in the game, it's really important for us to look at all these metrics or trends that we see in the market. So with the sports season, what we see is there are different sets of people who bet differently. Some people like to bet during the sports time, some people like to play the game before the game happens. Some really wanted to see across multiple competitors and then actually place a bet. And so there's a lot of trends that we were able to uncover using these tools that we have right now. And the one interesting fact is that probably we see a lot of people betting during the game. That was really interesting.
Zachary Bricker:
Yeah, I can imagine it's maybe not an expected outcome. You would think people are betting more before the game happens. Not I guess as the game is ongoing. Although I guess as we're speaking about predictions, there's probably a lot of predictive tools that people are using or that are commonly used across the different sites and different competitors that are evaluating sort of up to the minute odds as we sort of see with some of the different competitors, at least here in the us. So that's really interesting to see that you're seeing that uptick in people using predictive analytics and they're consuming it and they might not be performing the action, but they're consuming it during the game and maybe they're probably not doing it consciously other than taking a look at it. But that's a really interesting thing, how much that sort of predictive piece is impacted not only the population in general, but also how you look at things and how your team identifies potential. So as far as that goes, we're kind of talking about that now. We're talking about data-driven decision making as we're watching the game or as we're evaluating anything that's giving us that sort of constant feedback. We're doing a lot more data-driven making. In what ways has the use of Looker Studio transformed decision-making processes within the organization, particularly in terms of optimizing marketing spend across different channels?
Gokul Prasad:
So the use of Looker Studio has significantly improved our decision making process internally. So rather than just focusing on the primary KPIs, we now have the option to look at the campaign performance at more holistic level. We have more metrics pulled in, which was not available earlier. So what I feel is the comprehensive perspective is really crucial in aligning our PD strategies with our business call and with the implementation of Supermetrics almost we have 25% more metrics for all the platform, which was not available. And rather than just focusing on pure conversion trades or conversion KPIs, we now can see the impact of overall brand awareness at a holistic level, which is really good.
Zachary Bricker:
Oh, that's excellent. And any kind of, I imagine you do as far as budget planning, have you started to use Supermetrics in any way that would say where you're planning out those campaigns? We've talked a little bit about your omnichannel reporting set up there. Do you do any budget planning or predictive budget planning based through the Supermetrics data?
Gokul Prasad:
Yep. So back to the previous question, like I said, we do a lot of predictive analysis and we use a lot of customer trend analysis. So what happens is there's a lot of views where we look at past your data and we also merge our internal data as well to see which tactic or which campaign performed greatly and what drove business results. So what we basically do is we take all this data into one platform and make sure that we give the right solution or the insights to the business leaders to make actually the right decision for the brand.
Zachary Bricker:
Excellent, excellent. And so we're talking a little bit about that data-driven decisions and you're mentioning, Hey, we're rolling this up to the stakeholders as far as maybe a VP or hiring maybe all the way up to a CMO or something. And one of the things that we start to see in the market, especially when we are talking to higher level people, is all of the talk around privacy, right? You've got GEPR in the us, we've got the California Privacy Protection Act, and there are other protection acts that are sort of springing up all across the globe. With that increasing concern about data privacy and ethical use of customer data, how do you ensure that your analytics practices in Looker Studio adhere to what we'll say is regulatory standards and maintain customer trust?
Gokul Prasad:
So we have a dedicated privacy team who helps us a lot. So whatever we do on marketing is all privacy compliant and we make sure that none of the PIA data is involved in any of the analytics we do. So like I said, all the data we use on Supermetrics is actually coming from the platform, which is strictly privacy compliant. So most of the times we never deal with any PIA data for any of our media analysis, which is good. And we also have partners who help us make sure that we are in a privacy compliance space. So we have regular audits of our data to ensure we actually keep track of what's happening in the market and we are compliant with it. And recently we started thinking about having a unified consent management system, which we are on the background work. So probably that will also help us improve more privacy safety in place.
Zachary Bricker:
That's excellent. That's great to hear. Especially as you mentioned before, we're working with OLG, which is a government entity, so I'm sure that that's sort of something that's very top of mind for you, your staff and obviously the people, the stakeholders and everybody that you're reporting to. Walking back a little bit, now that we've sort of gone over the overview, we can see, hey, here's how we use these insights, what your predictive analytics and trends have led to and how you're rolling that information up to the data-driven decision level. Would you able to maybe not quantify, but qualify what the business impact of having a tool like Supermetrics is having that ability to bring everything in versus either having to do the CSV shuffle of getting all of this data in, or in some cases people or institutions roll their own where they have to build out the API. So do you have anything you could tell us there about the business impact of that consolidation and automation, what that's done to enable you, your team, your analysts?
Gokul Prasad:
Yep. Around we see a lot of improvement in report automation. So we have almost 75% more reports going out from our team once we started using Supermetrics. I believe comparing the data sources, I would say probably 80% improvement in number of data sources. And like I said, the number of metrics significantly improved earlier. We were only able to gather the primary KPIs or the ones we see normally on a platform. But with Supermetrics, I would say that close to 30% improvement in additional metrics, which is huge.
Zachary Bricker:
Wow. Yeah, that is huge. And especially, I know you mentioned the one number, the first one you mentioned there, 75% additional reports, that's a lot of information that's coming into your stakeholders. Would you have been able, obviously there are other tools and competitors out in the market we're not the only one. When you were looking at other competitors, I know we talked a little bit about the depth of the connectors, how many you can actually get in there, did you pay any attention to the data, how the data was coming through, there are some that come with a normalized data or is it normalized a little bit flatter? Did that, did that play into any of the decision making process around going with Supermetrics or that ease of use or ease of analysis versus having to mue a lot of data to run a ton of SQL queries?
Gokul Prasad:
Yeah, so when we initially thoughted about migrating to liquor through Supermetrics, we actually had an exercise where we worked as a team, gathered all the paid and earned and on media channels, what we have in a sheet of paper, and we decided, we actually looked at competitors of Supermetrics to see what options we have in the market. And what happened is we saw that most of the platforms we use or we use for advertising is actually available on Supermetrics, which was primary one of the reasons why we decided to go with Supermetrics. And like I said, we also tried a trial period during that phase where we actually started using the product and we actually pressure tested the product a lot. We actually pulled in a lot of reports and that's when we've realized that okay, the product, the technology behind it is really good and we didn't have a problem during the test phase, so that's when we decided to scale it and actually launch it across the massive campaigns we have.
Zachary Bricker:
That's amazing. And how many people are roughly actively using Supermetrics on your team at any given day?
Gokul Prasad:
I would say on an average 10 to 15 people actually use reporting coming out of Looker. That's possible due to Supermetrics. And it also depends on what timing we are on. Sometimes during the planning, that's when we will have more people on the dashboard. And if it's like an off season, probably we'll be looking at more deep dive sessions on these dashboards.
Zachary Bricker:
Amazing. Amazing. When you say these sort of deep dive sessions, that's an interesting case. What do you do during those sessions? Is it where you're going through some very in depth reports and kind of picking apart and looking for those little nuggets of insight, or are you analyzing the report quality itself?
Gokul Prasad:
So what happens is sometimes we see a flat trend in the market and looking at the primary KPIs or the general report that we receive, we are not able to uncover any insights around that. So that's when we do deep dive sessions around, okay, is the creative the problem or what is it causing that flat nature of the trend? So that's when we actually deep dive into multiple aspects of media. So we look at platform specific data, we look at tactic level data, and we look at creative level data. And actually we try to go much in depth based on the problem. Sometimes we even look at what's the audience target doing or how they're reacting to these ads, and we actually gather a lot of insights based on this deep dive to actually make a decision for the next phase of the campaign.
Zachary Bricker:
Excellent, excellent. These reports, I've been really interested, sorry, hearing you talk about them and sort of how you utilize the tool in order to bring these insights forward. When you're building these reports, what kind of approach do you take? Is it more of, I know you said that everybody has KPIs they have to hit. Are you focused a lot on we have to present these KPIs, or do you go into more of a storytelling where you have a question or a stakeholder has a question that they need an answer to and you go through and you build out the story of what is currently occurring? What's your process like there?
Gokul Prasad:
So what we usually do is we actually talk to the internal stakeholders. So first we try to see what problem they're trying to solve. So in the initial conversation, probably the analysis we do is more on the storytelling side, like explaining this is how it works, this might be the reason why this is happening. So more on the storytelling side, once both the parties are comfortable and around analyzing the data and they feel like, okay, this data is helping them to make an informed decision, that's when we decide to go for more an automated approach where we will schedule in some reports for these parties and they're also comfortable seeing what they have on the dashboard. So like I said, the problem in the current market is actually data is available everywhere. It's really up to what data we are looking into matter. So that's where I feel like we take a two-prong approach here where we actually have a storytelling in this initial phase and then we move to a more automated way of working.
Zachary Bricker:
Incredible. So as far as the automation piece, we've talked a little bit about that. How much time do you think the automation has saved you overall rough estimate? And as far as automating, we're currently, we're automating these reports. You're talking about how you set up a report, you tell the story, you build a dashboard to answer the question, and you put that on an automated schedule to go to the stakeholder. What does it look like in terms of we've decided to automate this is how much time it saved, and then we're also looking to automate these things in the future. Do you have a future plan of, Hey, we have this now we want to go here with our automation, this is how far we want to scale with it. Are you currently happy where you're at?
Gokul Prasad:
I would say we are actually trying to push ourself to actually have more automation in place. When I started working with lg, we were actually working with a lot of CSPs and Excel sheets, pulling out information from multiple platforms and combining it. Sometimes we have agency partners who will support us in terms of insights and analytics, but what we really did is actually making sure that we save a lot of time from these processors. Like we have one dashboard that basically collects all the information, filters it out, cleans the data, and it's available for the stakeholders in an automated way. So I would say we were able to save close to 30, 35% time in just processes involved collection of data, and we definitely have plans to scale up the automated reports in future.
Zachary Bricker:
And I guess what plans in terms of, are you looking at when you're saying you want to scale that up is from the data side sticking with that, what are some of the efficiencies and additional automation you'd like to perform there?
Gokul Prasad:
So like I said, it's always about pushing ourself and our team to make sure we have the right data to take the decision. So what happens is once we start at these deep dive sessions, we tend to see that, okay, this KPI is interesting, let's start monitoring it. And we keep an eye on that particular KPI for some time and we see how it fluctuates with the market trend. So probably I would say it really depends case to case, but overall the data that we get in one dashboard view really helps us to keep a track of it.
Zachary Bricker:
Awesome. Awesome. Thank you. Thank you. That's a really good insight. And are you currently looking into different data warehouse technology, you sticking? Have you picked one out or do you currently utilize, what are you currently doing there as far as data warehousing?
Gokul Prasad:
So we are exploring the options around data warehousing. So we are actively working towards building something internally where we have the option to blend in multiple data sources. So we have plans of doing it, but like I said, we are on the journey towards that.
Zachary Bricker:
That seems kind of like your logical next step. Once you have the reports down and everything, then you can start to pull all the data into the data warehouse and then it starts to become, I can do more predictions, I can use more machine learning and other tools where it requires sort of that a lot of high volume of data. Awesome. Well, so thank you so much for joining the Marketing Intelligence Show, Goku, it's been an absolute pleasure to have you here on the podcast today. Any parting words of wisdom for our listeners?
Gokul Prasad:
Yeah, thank you so much for having me. This was a great conversation. If any of the listeners want to reach out, you can find me on LinkedIn and I really wish all great luck to the marketers out there.
Zachary Bricker:
Awesome. Well, thank you so much. It's been a pleasure. Really appreciate your time here today, and I look forward to seeing your organization's data journey continue and prosper.
Edward Ford:
Thank you for listening to the Marketing Intelligence Show brought to you by Supermetrics. If you're enjoying the podcast, then we'd love for you to tap that subscribe button, leave a review, and share with your colleagues and peers. We'll see you in the next episode.

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