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Data-Driven Marketing for Authors: Using Analytics to Optimize Your Campaigns

Okay, guys, I believe it’s about time. So hello, everyone. And well thank you very much for joining us today for this new episode new webinar from my Joel ncid. As you probably know by now well, we’ll focus on the marketing side of things, and more particularly on how to build 300 to 360 degree view of your marketing campaigns. In a nutshell, the idea of today is well to discuss kind of the importance of data driven marketing, and how essentially can help you better understand your customer and increasingly competitive global markets and to address this topic, so we have with our divisions are from nine, who will will let himself introduce himself,

I Xherdan. Thanks for the introduction, I’d be tempted to say Hi, everyone, and thanks for joining this webinar, I partner manager, Vietnam and the forum taking care of the relationships of our partners based here in the EMEA region.

Thank you for Chenzhou and we also have today Cordelia, which is one of our experts, and Nigel and who will kind of do the wall, we’ll do the demo today. And myself, Julian, who is in charge of the UK operations. So before we start, I want to share today’s agenda. So we are going to start by presenting a data analytics ecosystem that we’ve put in place to address well data driven challenges. And what it is, and what it is it’s actually essentially a combination of expertise.

And two solutions that we are going to leverage for today’s demo, which are nine and Tableau Software. And we’ll present that to you in a second, we also going to go over the importance of data driven marketing. So we’ll talk about the concept of it. And move on to Well, the main objective for today, which is to illustrate all that customer use case and demo. And finally, we’ll keep some time at the end to answer any questions you might have, which you can ask during the the entire demo the entire webinar through the charts. So let’s get let’s get started. And the first part of this data analytics ecosystem is module and module is a consultancy firm that specializes in data analytics. So all that we do kind of revolves around data and essentially helping your customer create value from the data.

That can translate into a number of things like support in building a data analytics strategy from scratch, maybe help in choosing and deploying the right business intelligence solution, project support on a specific use use case or training. And to achieve that, what we have, we have different partnerships that we can leverage, like the one with nine, but also internal expert with various profile and expertise. And that really allows us to work across a wide range of industries and department. And you can see a quick glance here on the right with the various customer that we’ve worked with. But today, today, we’ve decided to focus on two solutions, which are, as I mentioned, nine, and Tableau Software.

And we did we do that now because they work perfectly together. But these two solutions combine addresses the two main challenges that most people and businesses will face in their data journey, which is, which are data quality, and understanding your data to make better decision. And the data value lifecycle which is illustrated here is how we at my job, we approach most of our customers data projects, it highlights all the states all the steps and stages for creating value around data, which can ultimately be split into two main categories with data preparation on one side, and data visualization on the other side. And the idea is that we are going to start with the business user, you are that person on the right of this illustration.

And you’re going to be asking yourself some key questions about your business, in today’s case, about marketing. So it could be about how to increase your customer engagement, how to monitor my brand image or maybe a little bit more related to today, how to measure the ROI of marketing campaigns across all the different channels. And essentially module is here to help you find answers to these questions by leveraging your or data and making it go through the various stages that you can see here. So that we’re going to talk about the two solutions.

And I will now leave Vicenzo talk about nine Vicenzo The floor is yours.
Thanks. Thanks, Julian. So how do we are, can we help companies to survive and maximize their ROI at night, we build software to create a productionize data science type of projects using one easy and intuitive environment. And this environment allows or enables also every stakeholder that is part of or takes part of data science of the data science process, to focus on what they do best. And, and to disregard what we develop are to complement complementary tools.

One on one side, we have an open source solution and free desktop version in DCs nine analytics platform, which is an open solution team intuitive solution that allows users and individuals to understand data and and also allows them to design data science workflows, and reusable components that are done accessible to everyone. So nightmare to start from, in short, allows you to handle the data science creation, to take part. So everything that goes around blinding and transformation of the data, machine learning model training, as as well as visualization. And on the other side, we have more the productionize production isolation, let’s say part that involves the usage of main server, which is an enterprise software, 14 based collaboration, automation, management and deployment of data science workflows.

And those can also use it you can use an IMO to allow or to enable the communication to other to other systems that are available in your organization’s one of the benefits of using KNIME as well is to enable non experts or to give access to non experts, data science experts by bad web portal or also via RESTful web services. Yeah, that’s that’s, that’s it from my side. Thanks, Julian.
Thank you, thank you very much, the Shenzhou somebody moving on to Tableau which is the last solution I will present you today. So you might already be familiar with the solution. Or maybe you’re already using it or even a similar visual visualization tool.

But Tableau is one of the leading data visualization tools on the market. And to put it simply, its mission is to help people see and understand the data. So kind of using a drag and drop technology is going to be very easy to use and intuitive. And that’s one of the reasons why we call it self service bi, the meaning that a little bit like not everyone, regardless of their technical background can autonomously and quickly answer the questions with data by building dashboards. So to summarize, Tableau makes data easy to consume. And we’ll show you that during the demo, an example of an analysis.

So we wanted to, I think, next session, we want to spend a bit of time talking about those two solutions and our approach to working on data project because one of the things that we’ve noticed is that the studying and actually a lot of studies show is that the biggest challenges in becoming data driven is number one, insufficient technology. And second, the lack of internal experience. And I think that’s one of the reason why we wanted to present to you module name and Tableau as one data analytic ecosystem. But that being said, let’s move on to the heart of today’s presentation and talk about why it is important to adopt a data driven marketing, marketing strategy.

And I think it’s hard to argue against the importance of data when talking about marketing, especially these days where while everything is connected, everything is becoming more and more digital. And of course, trends are changing rapidly. So no matter what industry you’re in, or even the business size data is today impacting how you operate, and your go to market strategy. And if we could do an entire webinar just on why big data driven is potent, I wanted to highlight three key benefits. And the first one is giving access to information and how this will empower marketers. And how empowering marketers to access and consume, while reliable data would allow them to uncover new insights.

Very importantly, whatever the need is, which ultimately will lead to not only faster, but also better decisions. So, key business user will gain kind of an understanding of the larger picture would allow them to monitor and keep up with marketing trend to finally of course, improve messaging, the products or, or the services. And for this webinar, and the demo that will shortly follow, we wanted to discuss your real customer use case to kind of make it a bit more engaging. And for that, we’re going to be looking at the company called Kroger, which for full disclosure, we’ve changed the name to respect his privacy.

But Kroger is a b2b communication agency that supports a wide range of customer in their obviously communication project and marketing projects. They do tend to specialize in the luxury sector. And they focus on five main activities, which are digital marketing, design events, and prints. And what you’re seeing here is the catalog of products and services that they offer to the customer, which I’m sure might seem or might sound familiar to a lot of you who are in the marketing space.

And the marketing department of Kreiger essentially contacted us as they needed some support in building a holistic view of all their marketing activity and make sure that they remain efficient at delivering their promises to to their customers. And to give you a bit more context to the project, and while the solution that we’ve deployed that Cordelia will show you in a few minutes. So the context is that Cragar is a leader in its markets. But as many other businesses, there’s a lot of new players that are emerging, which are of course, challenging their position. And of course, they want to maintain that position. So one objective that they had and were struggling to achieve was to create a 360 degree view of their marketing campaign.

A lot of monitoring and analysis were being done in silos and with, with campaign kind of evolving, and evolving to multiple platforms and channels and channels, that was becoming more and more problematic. So they needed to understand the larger picture, understand what worked, what didn’t work, identify where they needed to focus, where they need to invest, and so forth, and so forth. So what we did is, we work with them in deploying a monitoring tool for them to, to have, and we did that, but first looking at the data they had, how we could leverage it.

And yeah, essentially working on making it reliable and accessible for future further use and further analysis. And the second stage was to work closely with the various business user to define the right KPIs, which is kind of crucial part of the process. They are the ones who knows their business the most. And they are the ones who will be leveraging the solutions at the end to make the decision. So it’s very important to involve them. And then together, we built an interactive dashboards so that they could monitor and manage all of their marketing activity efficiently.

And very importantly, in real time, which we’ll show you in a in a second. Just before we go, we move on to the demo. So the size I mentioned earlier for this project, we had to leverage to two solutions, nine for working on the raw data making, preparing it and making it reliable, dependable, and then the tableau suites of solution which are Tableau Desktop for building the dashboard to from A to Z and Tableau explorer and viewers for getting answers and sharing insight across the organization and even sometimes to customers.

So that’s it for the context of the project and I will leave Cordelia ticket from from there.
Thank you, Julia. Hello, everyone. So before diving into the dashboard realisation I would like us to have a look at the main KPIs that will allow our client Cragar to manage its marketing activity. So on this slide, please join me if you can move to the next slide. Thank you. So on this slide if we brought to light some KPIs that have come from multiple data sources. So on the left, we have a KPIs coming from Google Analytics, such as the number of sessions and the number of old and new visitors.

And on the right, we have information coming from the Cragar CRM, the number of leads, those who were qualified and even converted, and the revenue and costs. So in order to create our dashboard, we thought about a way to respect the marketing environment lifecycle. So first, the analysis of the visitors origin, which is very important information for Cragar, then the acquisition channel analysis in order to get to the lead, and then to get to the lead conversion.

And finally, we thought it would be interesting to analyze the revenue by company type and by country. So the ultimate goal is to visualize types of campaigns that are benefit to Cragar, but also those which are not. So doing, it could be possible to make a strategy decisions to stop them or reduce the scale of use. Because it doesn’t really make any sense to spend money in a campaign that doesn’t make any money, obviously. So at this point, I could show you the dashboard we’ve created for a cracker, which is regrouping all these analysis. But I need to put a little more suspense on the dashboard.

You could ask why? And the answer is because that nowadays, in a marketing environments, data coming from everywhere, like we said, CRM, Google Analytics, social networks, surveys, flat files, and so on. These multiple origins make it complex to link them all together in order to create a simple dashboards. So what could be a solution? To answer these multiple data sources? Let me share my screen. So a solution would be to use a tool to gather all the sources, clean the data and make it a reliable data source. In order to do the steps quickly, and in an easy, intuitive way, I use normal logics platform. Nine is a tool that doesn’t need any technical skills to be manipulated.

It’s mostly a drag and drop tool. So digging in criteria has three types of sources, Google Analytics to get SEC traffic in CRM to get leads information, and flat files coming from monthly surveys, you can see all the three data sources are in orange, blue, and purple on my screen. So now has the ability to connect to all three data sources in parallel, thanks to specific notes. So let’s see a bit we have the first part by Google Analytics, and we have three nodes.

So the three nodes allows me to connect, authenticate to the source, and create and create the query I need. So if we take a quick look at the query over here, so this is the configuration panel, and we see on the left that we have all the data I wanted to retrieve classified in dimensions and in metrics. Let’s say if I want to add a field Sorry, I just need to look into this drop down menu for the field I want. Select it, for example date, and click on the Add button. We can see now that the date has been added to the dimension I want a query to look for. There are other options below but I don’t want to talk about it. Otherwise, the webinar will likely wait too long. So moving to another connect data connector, we have the DS and reader.

The generator allows me to retrieve the data from this yarn, which is on for JSON format, which is web format for data. And finally, we have the last the last node I use the list file, which allows me to look for files in a directory, which have the stored pattern in their name. The rest of the workflow was about cleaning and joining the data in order to create one single data source over here. And now that I’m connected to these three data sources, I’m I want just to collect it, join the data from a data source and pushing the clean data into a third party tool. Tableau Thanks to the new Tableau writer at the end of the workflow. So that’s it for the workflow of data preparation. Let’s go to the dashboard. So here is what we’ve created for Cragar.

So this dashboard is in the format that we met will call a data journal. Having a couple of years of expertise might write created these formats for analysis, and is a pioneer in this kind of representation. The idea is to start from a global overview at the top of the of the data journal, about our main KPIs and then to divide the dashboard into some subsections with their own topic, so we can easily dive into the analysis According to multiple axes. And here are the ones I mentioned just before, so the visitors virgin leads information and information about the revenue.

So let’s start with the top of the data journal about the global overview. First, we have an indicator at the very top about often on the period over which we want to make our own analyzes, here we are on a three year period, we have the possibility to change that period, thanks to the slider just below. And if I change the parent do period, all the graph from the dashboard will be adjusted on the new period analysis, just like it. Let’s go back to our full three year period. Just below the slider, we have our first analysis over here.

This is the KPI overview we talked about earlier. So we have the number of sessions over the three years period, the number of old and new visitors. So just to be clear, an old visitors have visited or have already been on the crag website and have saved it informations. A new visitor is a visitor that have never been registered on the website. Moving on, we have the number of means. And thanks to the tooltip we can have more informations.

So we can see here 2197 versus 4608 leads, the second figure corresponds to the target figure of least that was fixed by the Spirit. So at the end of the three year period, crago managed to get to 48% of the target figure. In the same way we have the number of qualified leads, which represent 55% of the target figure. And among those qualified leads to convert leads, which represents 61% of the target figure. Below each KPI we have the corresponding evolution curve on the analysis period. These curves allow us to detect seasonality effects.

Thanks to them, we can see there are some strong tendencies. For example, if I’m looking to the convert leads, it seems that there is a strong, strong tendency during the offseason and in winter. Thanks to the little filter, just hitting over here, I can select a specific month. And filtering by months allows me to have an overview of the evolution on a specific month for all the years. So an interesting analysis would be to filter on March, since its corresponds to the first COVID locked down in France. The result here, we have a complete field full of leaves. And I would say for April would be the same.

Yep, we have a complete full of these. So let’s go back to a full year analysis. Let’s hide this little filter and move on to the visitors analysis. The second part. So on the second part, we’ll dig in a little more into the visitors information. Let’s start with their origins by looking at the donut chart on the left. Over the three years period we had for 14,260 visitors, which includes old and new visitors. And thanks to the donut chart, we can see that 39% of the visits work come from no social networks.

Well, it could be interesting to know the distribution between new and old visitors. Right? Well, we thought about that a little bit before. And we have already included these fees in the tooltip. By hovering the social network part of the donuts we can see that what we call a vis invis. It’s simply a graph in a tooltip. So also shown networking most of the 4600 88 visitors are old visitors. In the same way, through a search engine for instance, we have a strong tendency for new visitors. So this information might be interesting for Krav Maga that could maybe increase their publicity through search and gene to get more new visitors. But what about analyze analysing the origin of visitors but this time through the type of acquisition channel.

So, like, just like Julian told you earlier, there are multiple acquisition channels, marketing, digital design, event, and print. Each channel have different type of campaign. For example, Krakow query, organize webinars or conferences on the event channel, or print advertising, posters, flyers, or magazine with QR codes for the print channel. So on the on the graph on the right visitors by acquisition channel, we have a bar charts, and each bar represents months. So for, for instance, in December 2018, we had 14 campaigns of marketing that lead to 180 visitors, visitors are still all new visitors.

And if we take a closer look to the global overview, we can see that the marketing channel has a positive evolution. And whereas the Design channel has less and less visitors, and that the print channel had complete downtime, starting on March 2020, this could be also a result from the beginning of the COVID lockdown. So now that we have more information about our Cragar visitors, let’s go deeper into the leads over here, the idea is that a visitor comes to under Cragar sites becomes a lien and that this lead can be converted into a client. So at first glance, we can see there is a color correspondence between the visitors by acquisitions on the top on the right, and the leads by acquisition channel graph. For example, light blue is for marketing. And channel information is also in the tooltip. Just in case.

We can see here that for the marketing channel, lead generation is the more profitable in terms of leads, since it has generating 405 leads. And it’s the more profitable in all the acquisition channels. For the print channel, for example, which is in purple over here, we can see the cattle have generated more leads in this is Channel and then QR codes. So if we want to analyze the relevance of QR code campaign, we only have to click on the QR code box. And all the dashboard is updating on the QR code acquisition channel. So we can see the visitors origin and distribution over here. And we also see that the QR code campaign works more during offseason.

Maybe it’s just because people is going out on the streets during winter, because it’s cool. And during summer there may be on the beach on Montaigne. So there are no QR code anywhere. So it could be interesting for Cragar to increase QR codes campaigns during offseason done during high season. So now, I would like to take a look to the event channel. So I’m going to click on it.

Of course, the dashboard date itself on the events channel. And I I need to remind you that that there are two types of events in person events and remote events. Here we can know there’s also a tendency where we arrive if I select for example, webinars, I can see that women’s eyes are more efficient during a winter. Make sense since they are shorter, it’s cold outside, nobody to be honest, wants to go out on winter because especially if they’re chilly. And if I’m looking for in person events, let’s take a product launch. What can we see we see that a product launch are more during spring or summer season.

So thanks to this couple of physiologists and we know now now that compaign Sullivan’s highly depends on the period and in the season. So to move forward, let’s take a look at the possible graph on the on the bottom right on my screen. So here, the idea is to analyze lead conversion action. So it’s looked like that on a global scale, mailing nurturing and demo are more likely to convert lead. And when a lead is conversion, a contract is signed, and there’s, there’s revenue. So let’s move on to the last part of this dashboard, which is about obviously, revenue.

So we have three graph, the first one on the map, we can have a quick look at the revenue distribution between countries where cargo has business, the darker the color, the higher is the revenue. So it seems like beside France, which has a large amount of revenue, it seems that Spain and Italy are have the major activity. And for example, Romania, have bi do not have a lot of activity. What could be interesting would be to compare the countries according to their campaign, the company news just to see if a type of company works more in a country than in another.

So the second graph allows us to do it, it allows us to compare acquisition channel according to the revenue generated. So on the global geographic scope, marketing is on top positions with more than 9 million euros of revenue over the last three years. And well, green tend design, well don’t didn’t really make a lot of revenue through the three years period. Finally, on the last and least we can make here is a ranking of campaigns according to the revenue so that this graph is a bit peculiar, because we can have at the same time, the top and the flop campaigns, so the best campaigns and I would not say the worst, and then not that good campaigns.

So I add things to the parameter over here, I can set the parameter of this top and flip, so like to like, make it short and select three. So on the global scope, lead generation, have generated almost two millions, euros, and we can see that conference didn’t really work that was not really profitable, since even in Krakow lost some money. But maybe what we can do is filter on a country. So let’s say we select Spain, which has quite a lot of activity for Cragar over there. So I’m selecting Spain. So my dashboard is updated. And we can see that the generation leads are still on top. But we can see also that Kreger is losing money, not only with conference, but also is profitable from fair and packaging. So maybe progress should probably stop organising conferences, professional, fair, and even packaging in Spain. We could also filter on the company type.

So let’s choose to digital acquisition channel, which didn’t really make a lot of revenue. Let’s see what’s happening. So clicking on digital digital acquisition channel, we can see that even though the digital channel didn’t make a lot of revenue, we can sit a Nam of the campaign made a negative revenue. And retargeting now is the best campaigns in terms of revenue. So well, we are at the end of the demo. This is it for it. I hope you liked it. And now I let Julian take back the microphone and press you on the presentation.



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