Using customer data as a fuel for personalization

we have a commercial director at Ematters, who has been working at the forefront of marketing technology. As a part of Ematters, he has successfully deployed personalization campaigns for many European organizations. Now, I’m a B2B marketer myself, but I have also been a B2C marketer. So, if there’s one thing, that invariably features in the priority list of all B2C marketers. That’s personalization.

All B2C marketers, I think are equally worried about personalization. It features in the priority list of all B2C markets invariably. But unfortunately, although personalization has been in the news for so many years, it’s like a classic point. Everybody tends to like personalization, but nobody really understands it.

Even if they understand it, there is an awareness gap. They do understand the post-consolation, but they’re not in line with the standard technical part of how to really deploy it in the organization. Okay. So in this webinar, we have invited Daniel to share a few personalization markets from his years of experience. As I said, Daniel has been deploying personalization campaigns for various European companies through the organization. In this webinar, he’s going to share how to put customers at the center of your personal efforts. And explain that by sharing examples from companies like Domino’s, ALDI, and Opel. So on that note, and without further ado, please welcome Daniel Nokes. 

Daniel Nokes:

Thank you, Ajit. and, welcome, all attendees this afternoon at lunchtime. So not too hungry, hopefully. Well, today, I will share my vision on marketing automation and data. My name is Daniel Nokes, a commercial director at Ematters, and I’ve been working in the fields of technology, data, and marketing for the last 12 years.

At Ematters, we orchestrate data in a complex and connected world. And for us, that data is the basis for personalization. Ematters itself was founded 15 years ago, as a digital marketing agency, evolved into a marketing automation agency in the last 5 years. Currently, we are focusing on data as the fuel for engagement and marketing. We work on a strategic technical and operational level with customers like, Ajit mentioned, Domino’s Pizza, and Opel. In order to show how you are able to personalize with data, we have a few examples to share in this presentation, as well.

A:

Before you proceed and, you know, before our audience goes deeper into the webinar, I just have a few, announcements to make. So folks, while you are enjoying the webinar and going through it, please feel free to ask questions at any point you have via the go-to webinar panel.

Also, towards the end of the webinar, we would also allow attendees to share the questions verbally directly with Daniel. Currently, you folks are on mute. But towards the end of the webinar, we are going to allow you to ask your question. We are going to allow you to unmute yourself and ask questions directly to Daniel.

Please feel free to ask as many questions as you want. Toward the end of the webinar, we are going to take all of the questions, all of those questions at once. Yeah. So that’s all from my end.

DN:

Great. Thank you. So what are we going to talk about today? We are talking about putting the customer really, truly first, at the center of your personalization efforts. You have a lot of data. I assume loads of it. But a lot of organizations don’t know how to use it in good order. Which data are you going to use to ensure that engagement and conversion KPIs are actually achieved? And how do you collect this data on a recurring basis?

How do you keep it updated and enrich it? So today, we are centralizing the customer and trying to show you how you can use data for personalization purposes. 

So a few items I would like to share. We will start with today’s consumer. So it’s about you and me, just as people in the Netherlands, Benelux, Europe, or the world.

We are the starting point of all marketing efforts and we want personalized content. So we need data. We will show how to overcome and simplify data challenges with examples from practice. And we will finish the webinar with a few needs to no takeouts. If you ask me. But let’s start off with you and me.

What’s my behavior? What’s your behavior? And what are our expectations? Let’s have a look at a regular mobile phone, you see apps like Spotify, Netflix, and online banking in the Netherlands with ING. You see online groceries with Albert Heijn, and Uber for food and transport. These companies are digital-first. Therefore, they offer a highly personalized and convenient experience, and that’s the baseline for us as a customer for our expectations.

So we need to align these expectations with our own marketing activities, and that’s quite difficult. When you see, research in regards to consumers. Consumers expect personalization. Nine out of ten consumers say they like personalized offers. Over half of the consumers even expect personalized content and research shows that 80% want personalization.

When you look at consumer behavior and consumer research, it’s a hygiene factor for personalization. It’s not something cool anymore. It’s something you need to do as an organization. And the funny thing is that when you look at our personal personalization and activities with our customers, we see the effect. We see that it works in practice.

This is an example of Opel, where we start off with basic personalization. Normally, we send out a monthly newsletter with quite good, opens, and click-throughs. But when we add one data point in the mix, the model of interest, you see that the KPIs almost double or even more. When you look at the click-through rates and when we add website behavior in this mix as well, you see that the consumer is excited about their relevant content and are willing to look at it. But it’s not only on email where you can see the personalization efforts. Website personalization is something that happens not often enough, I think.

In this case, with Opel, we combined both website and email. In one campaign, you can see a pop-in. It says special offers for you. But we have different pop-ins that we share with people who visit the website.

When you look at unidentified and identified website visitors, you see that we share different content blocks. When you are identified and part of the database, we share a message about the phase where you are in the sales funnel and we use email flows in this campaign as well. So when we know you, we say, well, go to the page that is relevant for you or we send you an email straight away. For unidentified people, we have two options. First, someone who was on the website before, but is not yet in a database. The first thing we want to gain is get that person in the database and retrieve first-party data.

So we offer specific discounts and try to get the people in the database. The second category is someone who is unidentified and wasn’t on the website earlier. Then we just have a general pop-in trying to convince them to be part of the database. We have relevant content blocks in the pop-ins and when you look at the results, the conversion rates of these pop-ins are great. They’re five times more than the regular pop-ins

You see that the conversions from marketing-qualified leads to sales-qualified leads are much higher than regular communication. Of course, the email statistics too. So we see that either when we use email or a website and personalized based on the data we have, we can increase KPIs. Another one that is really important is that over 50% of purchases are influenced by convenience.

Quality is more important than price, but convenience is a decision factor as well. When you look at generations, we see that Generation Z expects a low number of touch points, especially in contrast with the average nine touch points, a millennial expects. So this is an example of research from a big platform that says convenience is even more important than brand. It is not something I totally agree with, but it shows that the consumer is changing and expects convenience. Therefore, I would like to share an example from my personal customer journey. It was a bad experience with a great digital-first company.

And you see that there could be a misfit between expectation and experience. It could result in a stressful situation for a customer. In this example, I myself received an email with a last-chance discount. I went to the app and I tried to find a simple shoe for my youngest son. 

I selected one of the shoes in collaboration with my son. Of course, Zalando has my data and from that point, it gets interesting for me as a customer because now I have it in the basket. I’m trying to buy the shoe. I go to the ING app, then the customer experience breaks. There is no connection between buying the product and returning to the website. I’m logged out.

Haven’t got a clue, if there is a confirmation whatsoever. Then I receive an email with a confirmation, and afterward, I receive an abandoned basket email. When I return to the app, the shoe is still in the app in my basket. So this is stressful. This is not convenience.

This is something that we need to change with data as fuel. And when you offer convenience you bring convenience and personalization to the table. In this example in the sales funnel of selling pizzas, it works great because someone is unidentified, you can just share well. You can take, take out or you can deliver a pizza. But when you know me, you can offer my own personalized content. In the case of preferred pizza, we see that conversion rates in this sales funnel boost extremely because it’s relevant and personalized. 

The Third most important pillar for a consumer is omnichannel.

Consumers expect an omnichannel experience, even more post-COVID. Before, people went to the store or went online. Now they like a hybrid way of buying things. On and offline. When you look at research from Snapchat, for example, last year, it shows that a lot of customers like to get back to the stores. Yet, there is a new need. High-end technology and a seamless on and offline experience with AR or virtual services in the store. 

There are things that are wanted by the customers, especially Generation Z. Again, they are born in this world where they don’t know what it was before. And without noticing, we are already working with various technologies. This makes data collection challenging because think of the former old school QR code something which is used quite often currently in the catering industry, an easy way to connect on and offline, but where’s the data? What about IKEA with an augmented reality app showing the chair in the corner of your living room? The same technique flex our paint uses to show your wall with the paint of your choice. Extremely interesting data to collect and use in the follow-up customer journey. 

And user-generated content is used very often currently on Instagram and TikTok. But how do we track and tag people’s behavior in order to personalize the journey? Finally, live video streaming is something that has gained a strong foothold since COVID. So as a recap, we as consumers expect personalization with demand convenience. This is what we want. 

These examples of this connected world and the future predicted with web 3.0 make our life as marketeers quite challenging and quite difficult because how can we organize, collect, and update relevant data in order to give a perfect customer experience? 

Online data, offline data, data from external parties, first, second, third party data, and so on. So that is the challenge. We are still struggling and need to focus on and own a third-party straight data strategy but why and how is the question. So I would like to focus on the data part before moving on to the personalization.

In Web 3.0, everything will be connected. So the data challenges will get even bigger. So what do we need? We need a first-party data strategy before we can move forward with personalization. A question I get often is why data? Well, then I have a simple response, why not, because you will not exist anymore in a couple of years.

There are a few things we need to take into account when we get the question. Why data? One of them is market development. Owned data was always important, but now in 2023, you’re going to need it. Companies that have a first-party data strategy are more successful than companies that haven’t got a first-party data strategy.

With companies like Google saying they will end the third-party cookie and Apple saying that there is no more tracking in iOS 15, these kinds of market developments will push us forward to get that first-party data strategy. In combination, research from McKinsey, in this case, shows that marketers have a great challenge with data.

Say that they have a challenge collecting, integrating, and combining data in their own organization. Of course, the other one I mentioned earlier is how can we combine online and offline behavior in favor of the customer. It is difficult, but necessary to combine both data points in order to personalize and be relevant. You need to get that right message at the right time and don’t want someone visiting the store to receive an email when he or she just bought a pair of jeans or shoes. So what do we need? We need organizations to focus on data.

And this is a challenge because, within organizations, there are two challenges as well. Data is not always an integral part of a company’s strategy. We need to focus from sea level down to operations and create awareness of the importance of a data strategy. When the third party’s cookies disappear, you need first-party data. Otherwise, you are not able to personalize in the way you would like to personalize.

In addition, as a company, you want to get to know your customer or future customer in order to personalize. We need insights into what their needs are, and where they want to go before we can be there for them. And, of course, the efficiency and optimization in marketing is an interesting one within organizations. In the longer term, you can accelerate your efficiency by using data and finally, you don’t want to be dependent on Google or Facebook.

It’s something everyone wants to change in their internal organization, and you need first-party data. But then we have the market developments. We have organizations that are still struggling. In addition, you need the technology as well. This is quite a complex item.

There are over 10,000 platforms currently. You have the CDPs, CRM systems, ESP, email service providers, market-automation platforms, and DMPs, you can go on and on with this kind of platform. What’s your ideal setup? Is it a best-of-breed or a full suite? Something which is key, because we can have that great strategy in regards to data, but without technology that suits your needs, we can’t do anything. So we have a lot of challenges.

I hope to help you with a few answers as well. Where should you start with? We should start small but with great vision and focus. I will share something, about our vision in this matter. 

For example, we have Sarah. Sarah is a consumer. We’re going to put her first, so we need a strategy, goals, and KPIs, which are an important part of the customer journey to create a golden customer profile afterward. We need to know as a company what our sales targets are, and what our engagement goals are, and if you want to focus on loyalty, then we can service Sarah best. So in this customer journey of Sarah, we can go from the orientation phase to a selection where you buy something in the transactional phase, have a delivery, service, engagement, and hopefully a reactivation, or, another buy in the near future. 

Sarah has her own customer journey. But what is important, where do we get and where do we need data. Because we need data to personalize and retrieve data for this purpose. I will share a few examples afterward. The question we ask is what data do you need to be successful in your company goals? This is the $1M question. What data do you truly need?

Because you have a large amount of data available. Perhaps, behavioral, multichannel, or external contextual, but we need focus. We can ask, tag a line, and add external sources, predict via predictive modeling, but we need to know what to predict, what data we need, how to retrieve it. 

Therefore, we have come up with the golden profile. In order to get focus, we use this model.

It consists of three levels of data. First, primary data, data you really need to communicate with consumers, In this case, email address, for example, or opt-in. Secondary is the data that helps you to personalize, perhaps where someone lives, the preferences that face in the funnel, and tertiary data is more deep-lying, data like channel preference, royalty, and COV. And we say that when we know that if we have retrieved this data, we will reach our sales and engagement goals. This will help us personalize but don’t forget you need to keep on collecting data, enriching data, and updating it to provide a personal experience.

This is something that needs to focus on. You need to get that 98% profile. But you need to have a strategy for this purpose. To give you an idea of what kind of things you can do, to fill your golden profile. I have a few examples.

For example, Peugeot, in this case, is planning to launch a campaign for hybrid cars and they have a large database with context. So we want to find out who is interested in a hybrid or petrol car. We just ask. we don’t know it yet.

We ask in an email which you prefer a hybrid or petrol car. A large number of opens answered this specific question. So we could easily follow it up with a relevant personalized campaign that people were already engaged with. So focus on that one data point, the type of car. Another example is set up, the question for a car brand is when will someone buy a new car? So again, we just ask on a website in a fun and engaging way.

This campaign runs continuously and feeds the ready-to-buy campaign. So when someone has indicated they will buy a car in 12 months’ time, the ready-to-buy campaign will run in 12 months’ time for this particular individual. In this campaign, we warm up the individual and personalize to get that sale. So we ask what’s the family composition? What kind of, size would you like? What kind of color?

And then, in the end, you had the perfect car at the perfect time. And, of course, within the welcome programs, and the welcome journeys you can do the same. It’s the same story, different customer. 

Play Up, a store that sells baby clothes, furniture, and accessories, What do they want to know in order to personalize? Is it going to be a boy or a girl? And who am I dealing with in this communication? Is it a parent, grandparents, or friends? What was the preferred style? These questions are all asked in the welcome journey via an online quiz. A lot of people are engaged with this quiz.

They enter the data, and we can personalize it straight away on the website and in email communication. And we keep it up to date. We don’t stop. We want to know if this situation will be the same. For example, by collecting online and indirect data, we want to know when things change, in order to use it in the communication we have. And this is all to get that lifetime customer from the orientation phase, where we don’t know the customer yet.

But with strategy and focus, you can get a great understanding throughout the years. So in this case, Sarah starts off in the orientation phase not really knowing her, but trying to get her to subscribe and register for a bit first-party database. From there, we can follow her and see what she does online, or offline. She gets a lease contract, but she is expanding her family and wants a bigger car, etc., and so on. This is a lifetime customer based on a data strategy.

To give you a practical example of that first-party data strategy, we have an example, of our collaboration with Aldi, the Netherlands. A company focused on creating a first-party strategy the golden profile. What data does Aldi need to be successful? A success for them is to gain insights, make an on and offline connection, and personalize content to boost store visits. This is an example set of the golden profile of Aldi.

And we said, well, how can we enrich this data? We said, well, let’s do an activation campaign where we focus on email, getting an opt-in, finding out what the status is, how often they come to the grocery store, and the category preferences like fish, meat, vegan, etcetera. So we defined it. We said, we wanted to do an activation campaign and collect these data points, but we organized, an online campaign during, the Christmas period. So in this campaign, we had a quiz where we asked, well, who is going participate in the Christmas dinner, kids or just friends, only adults, what are your preferences, fish, white wine, red wine, beer? And, finally, we asked them to leave their email address and opt-in so they could be part of the first-party data strategy as well. 

After this online quiz, we have the fuel to personalize straight away. So what we did in the follow-up is personalize each email with almost individual recipes, products, and a store near you. The engagement numbers increased immensely in this communication in comparison to the regular newsletters. When the date was almost there, Christmas, we started boosting more products, that were relevant saying, you’ve got to steer a store just around the corner. Finally, the really important one is we ask them after the holiday period if they went to the score store in order to buy the Christmas menu. And that’s an important one for a golden profile. 

We had a question entered into the email, and almost 35% answered the question. we had an engaging campaign. People who entered the database had a warm welcome. The golden profile was built, on a few, levels.

We had the email address, the opt-in preferences, family composition, and store visits. This is a really important one for Aldi because they have insights on their customers as well. They can use the data they receive straight away in the communication. This is something the organization tells on how to gain that data, how to update the data, and focus on reporting. So what’s the state of our golden profile? Is it 10%? Do we still need 90% or is it 70%? Then we know we will be more successful in achieving our goals. An interesting one, of course, is we’ve seen a few examples of database enrichment, database growth, personalization, and getting people to the store in order to, spend money, in the store. 

What you need in addition to the goal of the profile, is a brief, simple, focused road map with these kinds of activities on it. Because you need to make that strategy work and keep it pragmatic. Just to finalize, the examples I’ve given are a few personalizations in practice examples. And again, these are use cases for you to start small with. So you need to have that vision on data, but you could just start small and set small steps throughout time. A great example of something you can do tomorrow if you have the data and want to find out what it does for you when you use basic segmentation.

I think it’s the same story with the website personalization. If you have a feature in your platform to personalize the content on the website. Just check out what it does, when you use identified versus unidentified target groups. Are the KPIs going to increase like the numbers, I’ve shared? And of course, the basic segmentation, you know, you can make really complex, but there are a few basic things you can do.

You can start off with life cycle segmentation. So taking myself I’m Daniel, thirty-eight years old. I have two young boys, seven and ten years old. I live, in the Amsterdam area, and use that data in a simple way. Nike sends me an email, with a choice for kids.

The museums in the Netherlands. They sent me an email that there’s a kid’s week during a holiday period. And for concession, they shared family holidays with me, because they know I have a family and they go to campsites during the summer. And what you see in general is that when you have a relevant segmentation based on data, the open rate can go two times and conversion rates go four times in some examples we have. So this is something to test and use on short notice.

Another example is Poiesz, a well-known store in the Netherlands. They have a simple, proposition. They just ask me, what’s your next job in your home? Are you going to do, the bathroom, the kitchen, or the living room? And based on my answer, they offer personalized content and offers, for that particular room in my home.

And my personal experience is that these kind of straightaway follow-up campaigns are really successful. The only thing to take into account is that you need to make it scalable because the group will get smaller and smaller, in order to personalize. So you need to have different journeys that are scalable and multiply easily with the content you have available. Otherwise, it will not make enough money with the personalization, and that’s something, yeah, a lot of companies are looking at, of course. 

So, my bold statement is let’s go. What do we need to do? We know that the customer has high expectations. We know that there is data available, but we don’t have to focus on the data, so we need to take that focus. A few takeouts I would like to share with you, we really see it.

Personalization truly works. So experiment with it and you will see. The organization will need to invest in that part of the business. You need to start off with the first part of the data strategy. It’s as simple as that.

Our way of starting off with the strategy is defining your golden profile. What data do you as an organization need to be successful in your company KPIs? And finally, start small with a great vision, of course, but create successful use cases and share that success internally to be able to get more budgets, get more resources, and move forward from personalization to hopefully hyper-personalization in the near future. 

Thank you very much, for your, time. As Ajit mentioned, we have time for a few questions. If you have questions afterward, you can always reach me, at my email address or telephone number.

But perhaps over to you, Ajit, are there any questions, I should have a look at?

A:

Yes. Indeed, we do have, you know, some great questions. And I think this is my personal favorite as well. So, you mentioned a third-party case at the beginning of the session.

So, I am not getting the name. Yes. Charles is asking in light of the fact that Google is getting rid of 3rd party cookies, do you have an example of how companies are changing their marketing strategy?

DN:

Unfortunately, not yet. I was at Google a couple of months ago And even they said during, the workshop that companies need to focus on a first-party data strategy because they will not be able to use third-party data anymore. The thing is that data isn’t, a particular subject that is discussed on C-level within organizations. And I see that companies who have, people at C-level who are interested and understand, yeah, the goal of data, they are successful. And what you see is that they have a first-party data strategy where they say, well, we have a plan.

We want to have a lot of data. We want to gain focus and we want to update it frequently We want to connect new sources when we have new sources. It’s a really structured way of looking at data, and that’s an integral part of the marketing and sales strategy. It happens, but, unfortunately, not enough, if you ask me.

A:

Right. we have another question, I apologize if I’m not able to pronounce the name, right, it says White Cheslov. So White Cheslov is asking I think it’s a tool-specific question. He’s asking, what platforms allow basic email personalization based on website actions? Can you recommend something for a start?

DN:

Yeah. It was one of the slides where I referred to the marketing technology stack, which is quite, a complex subject. We see different levels of marketing automation platforms where you are able to personalize. Of course, you have bigger, larger platforms like Salesforce, Celigent, and Adobe, which offer a lot of options and modules. But there are platforms like ESPs – email service providers, who have that kind of feature in themselves and combine it with data too. We look at the kind of, you know, customer data platforms that offer email, automation, and loyalty in it too. You have platforms like Foyado, and Emarces in the Netherlands, and you have a mailing as a true ESP, but the thing you are hearing from me already is that you really need to find out what kind of platform suits your particular needs, and then you can make a decision on that level.

I’ve seen too often, unfortunately, that an organization just took upon a platform based on a few nice demos. And then afterward, it didn’t fit their own ambition in that field. And that’s a check you need to do beforehand. So give that platform when they give a demo give them a few use cases that apply to your future state of Marketing Automation And Personalization would be my advice.

A:

And, Daniel, of, the tools that you mentioned, like, Marsas and Adobe and the kind of tools that you mentioned, they are typically expensive. Right? They might not be feasible for a small firm. They might not be feasible for a small business to deploy. So imagine a small business wants to do email personalization. So in that case, do you have any names in mind that they can go after?

DN:

Yeah. Sure. Yeah. I think the ones I mentioned were the ones at Malyon originally from Germany was interesting. Of course, you have, a SendGrid, which can apply for the more easy, email marketing as well. And I would say, well, if you are interested in more names, you can always write me an email and I could just give you a list of, suppliers I know from that perspective.

A:

Right. Great. let’s go to another question. We have a question from, Virish. Virish is asking, how do you deal with privacy regulations in terms of storing personal data of business? Do you ask for consent before?

DN:

Yeah. That’s, of course, due to the GDPR and the APG in, Europe, You need to have the consent. that’s why the opt-in consent is one of the primary data points in the golden profile. Otherwise, you are not able to communicate with the person. Looking at consent, of course, you need to write down your terms and conditions and what you are possibly collecting and using, for the purpose of personalization.

But the timestamp, what kind of data you are able to use, that’s something you need to take into account. Of course, otherwise, you will have a problem.

A:

Yep. We’ve got another question from Aaron. Aaron is asking, how do you navigate to have consent and expand your first-party database with GDPR guidelines? A lot of questions from the point of view of GDPR.

DN:

Yeah. No. I can imagine, you know, that’s the funny thing about first-party data. There needs to be consent and consent needs to be clear. And when you have a strategy, a first party, the data strategy, and the data enrichment strategy, you can’t just buy a database somewhere and add particular data you’ve seen somewhere on the platform to the personal data. 

You need to be clear to your customer or potential customer what kind of data you are retrieving and what the purpose is of the data. And that’s the whole idea of the golden profile is that you don’t collect data that perhaps you will want to use somewhere down the road but you really collect data, that is relevant for your organization. Therefore, for the customer or potential customer because then you are able to personalize. So you have to focus on the data and it’s easier to explain why you are retrieving and using certain data. So it’s like, a safe way of using data and communicating about this to your customers.

And the funny thing is I think and see the projects we do with data enrichment. So the email example, for example, where we just ask someone what’s your preference. A lot of people, engage in these kind of questions, and that makes it easier for us to explain why we ask that question and use it in the follow-up communication because when you ask a consumer, do you want personalized relevant content, 9 out of 10, say yes, and that’s the basis of the GDPR, I think.

A:

Right. we’ve got another question from Yes. Give me a second. Yeah. We got another question from, the WhiteHatLab only.

So WhiteHatLab is asking how to test it. Okay. No. We actually got a follow-up question from Aaron. So, Aaron who asked the previous question, he’s asking again.

Okay. Have you mostly worked with one trust, Danielle? He’s asking that. Yeah.

But that’s not the kind of data. You know, that’s a separate platform, etc., separate data source. So that’s something you can’t just automatically use in setting up a golden profile. I think because then you are yeah, crossing the line of, GDPR regulations.

A:

Right. Okay. We got another question from and it is related to the answer that you gave just now. That is about the Golden profile. So, he’s asking how to test a Golden profile. Is it best or can it be improved?

DN:

So can you repeat the question?

A:

Yes. So I think the question is slightly confusing as well. So how to test a golden profile? And I think, you know, the other thing that you want to ask is, can it be optimized?

DN:

Yeah. It’s a continuous process. So it’s not something you just write down on a wall, and it’s there for 3 years’ time. it’s something you need to challenge each other with.

It’s something you need to update because, yeah, when I enter the pain at all, that database, the example, today, that in 9 months time, perhaps I, get a kid, a baby, and then, my situation is totally different. So you need to update the data throughout. And the example of Peugeot shows that sometimes there’s a question within an organization. We need to run a campaign on hybrid cars. And an easy thing is that we have that first-party data, and we can ask our database to answer a question on that particular subject and re-use it in the next campaign. So I think it’s a continuous challenge.

The only thing is that within the primary, secondary, and tertiary data, you have basic data you really need as an organization to personalize, but I think 80 to 100% is flexible, for the golden profile.

A:

Right. So that goes for the bachelor’s lab. Just letting everybody know that in case you want to ask anything to directly Daniel, feel free to ask directly. Right now, you are muted, but I can unmute you. Just let me know if you like to unmute yourself and ask anything to Daniel directly.

Yeah. So that’s the second question from. I think there’s one more question from, Bos, and he’s asking, any publications or books that one should read for becoming abreast with?

DN:

That’s a good question. It’s a good question where you don’t have a direct answer. I’m not really good with names, to be honest. This is something I need to look up but I have a few in the office. I haven’t got one top of mind, like a name, but, as mentioned, can have a look at the cupboards and share something afterward.

A:

Yeah. And I would also have everybody know that we are recording this webinar and the recording and everything and also the deck, the presentation is going to be shared with everyone. So I think there’s one resource that is going to be available to all of you, as far as resolution is concerned. And, obviously, we are going to ask Daniel, about the other resources that we should be reading in order to become abreast with post-addition.

And, I am going to mention that in the thank you email that I’m going to share afterwards. So that’s all the question that I had, Daniel, from folks. I think it’s about time as well. So, folks, if you have any more questions for Daniel, feel free to ask now. Additionally, you also have the email ID of Daniel as well as his phone number.

So I think, you can call as well, Daniel. When in case you’re calling him and just write to him, then you have his email ID as well. Feel free to write to him directly and ask anything that you have in your mind. meanwhile Daniel for this webinar, that’s all the questions that we have from from the audience.

Any final word before we call it off?

DN:

Thanks for being there. Would say if you would like to have a challenge or your first-party data strategy, we can always have a chat, and, hopefully, you will be able to focus on that, matter, data, and personalization for the next, quarters of your time.

A:

Yeah. On that note, thank you folks for joining. Truly appreciate your time, and I hope it was worth it. and, as I mentioned, I’m going to share the recording as well as the deck to all of you, whether or not you have attended. To all the registrants I’m going to be sending the materials.

So on that note, thank you so much for attending. Have a great rest of the day. Bye. Thank you.