Liberating the Data: How to Transform the Customer Experience
Ronit: Welcome to today’s webinar, Liberating The Data: How to Transform the customer experience. My name is Ronit Margulies and I'm the digital marketing manager here at BreezoMeter and I will be your moderator.
Before we get started, I wanted to go over a couple of housekeeping items. Today's session will be recorded and emailed to you afterward. As always, we will have a Q&A session at the end of the webinar. Feel free to send in your questions as they come to you throughout the webinar presentation as well as at the end when we have the Q&A session. The Q&A button can be found at the bottom of your Zoom screen. There's also a chat. If you by mistake send it there, that's cool too. We'll try to get to that as well.
I remind you again: if we don't get to your question someone will follow up with you after the webinar. For those of you that it's your first time with us on a webinar, BreezoMeter is a big data company that provides actionable personalized data for air quality, pollen, weather, and fires, to businesses from numerous industries as well as to governments, and consumers on our app.
Today's webinar will be hosted by Tamir Kessel Europe business development lead here at BreezoMeter. Tamir has over 20 years of experience in corporate and startup companies and business development and leadership roles. He's led and consulted on many critical enterprise transformation projects. Tamir loves growing and developing new technology businesses, teams, and partner ecosystems. He sees himself as a connector of people, processes, and ideas. Take it away, Tamir.
Tamir: Hi, everyone. Glad to be here. Many organizations today are trying to implement or already are implementing digital transformation initiatives. The question I always ask is, why are they doing that? Some are looking for a way to save money, some want to increase revenue. Some want to engage with a younger customer segment, and honestly some I think are doing it just because it's trendy.
Ronit: Well, Tamir, what do you think about digital transformation and how is it linked to data?
Tamir: Well, my view is well captured in the cartoon you see here. I really like to cut through all the blah blah on digital transformation. I find the term is overused. The hype around digital transformation means that many of these initiatives get lost. The projects struggle to navigate between hype and reality because they are focusing too much on the technology itself and simply copying what others are doing.
To me, there is much too much talk of digital transformation enabled by the latest technologies, and too often the technologies are driving the conversation and the strategy. To me, it's the business goal and the company's unique data that should be driving digitalization.
Ronit: But isn’t digital all about technology?
Tamir: Sure. However, it's not the tech that will transform the business. Yes, you need the infrastructure, you need the tools. But will simply implementing the latest tech or moving your business to a cloud infrastructure transform your business? Unlikely.
Ronit: So then where does one start?
Tamir: Well, we've evaluated what our leading customers are doing and how they have tackled the digitalization opportunity. What we found is that there's a common thread that runs through all successful initiatives, solutions, whatever you want to call it.
We've put together this very simple framework that can help in firstly identifying where digital really brings value, how business value can drive the choice of technology rather than the other way around, and how to identify your unique data assets and the best third-party data assets that will drive real personalization and truly engaging customer experiences.
Simply put, we start with the business goal. Then you ask, can digital address this goal? You then evaluate what data you have available and what other data is available. Then identify the relevant digital technology and experiment with the solution. Some people have said to me, well, these are the steps of really common sense. True. But then why do statistics show that 20% of digital transformation projects are succeeding? I believe it's about going back to the basics.
Ronit: Break it down for us, Tamir.
Tamir: Sure. Instead of starting with ‘oh that Big Data technology or IOT gadget is awesome and where can I apply it?’, we suggest starting with the business goals. What are you trying to achieve? What problems do you want to solve or what part of the business do you want to grow? Then you need to ask, can digital help solve the problem or reach your goal?
You need to then evaluate what unique data you have to help solve that problem. Every business has its data. It might be its sales data, it might be its operational data. This is unique to what it's doing. And then look at what third-party data can complement. At that point, you then go back and say, okay, what's the appropriate technology? It might be the latest AI or it might just be trusted Excel spreadsheets. And lastly, go out and experiment with the solution. Assume the first version will not be perfect but use the feedback to continuously improve.
Ronit: So what industries does it apply to?
Tamir: The framework can be applied across any industry really so long as you continue to make your business goal the priority and not the latest shiny technology.
Ronit: Can you give us an example of this somewhere where digital has a clear business value?
Tamir: Absolutely. Let's take the consumer goods industry, companies such as L'Oréal or Johnson & Johnson, both happen to be BreezoMeter customers. Like any firm, they want to create ongoing relationships with their end customers. However, traditionally, it's not been possible in this industry. These companies are classic B2B2C companies. In other words, they don't sell directly to consumers, they sell through supermarkets, pharmacies, etc. So traditionally, they didn't have a direct relationship with the end customer, the people who consume their products.
Their business goal is to build a direct relationship with their consumers in order to improve their products, get direct feedback, and at the end of the day increase their sales through these direct relationships. So can digital help them do this? Absolutely.
This is exactly what L'Oreal has done with their my skin tracker app. They've created an experience that is personalized and utilizes unique data. Data about your exposure to different environmental factors such as pollution and pollen. And through that, they're able to give value through digital and in return know more about their customers’ needs and have these direct relationships. All this without the traditional challenge of a retail intermediary. In other words, they don't have the pharmacy or the supermarket as an intermediary.
Ronit: And all the while creating brand engagement even when the user is not using the product.
Ronit: So how does a company decide which data to utilize?
Tamir: First thing to do is to look at what data you have. What is your unique core data, and then what unique third-party data can you use to enhance your digital offering? You need to find it, correlate it, experiment with it. Mix it with some AI and apply it to drive personal experiences that delight your customers and automate your digital services.
Ronit: Give us some examples here of companies who follow this route and how have they done it.
Tamir: Sure. Let's apply the framework to understand some additional success stories. We've identified some simple questions for each stage to help evaluate these use cases, and then we can jump into some of them.
So first of all, as we said:
Let's start with an example of ALK. ALK is a leading Danish pharmaceutical company that markets over-the-counter allergy medicines. Like L'Oreal, they wanted to better understand the customers’ requirements and to be the central source of information for their medical conditions. They asked themselves, what could digital do for them? The conclusion was to create an app that offers their customers information on the reasons for and symptoms of their condition.
Together, I call this liberating the data. Basically, identifying the data and then releasing it and letting it drive the experiences and the interactions with your customers.
Ronit: But is this only relevant to customer engagement business goals?
Tamir: So the ALK solution and L'Oreal as well focused on customer engagement, but the framework can be applied to any business goal or problem. Let's take another example. Let me break it down again stage by stage of the framework.
Ronit: That’d be great.
Tamir: So, we're working with another customer, with the marketing department of a large smart home appliance company, and they wanted to optimize their marketing spend.
Ronit: What do you mean when you say optimizing marketing spend?
Tamir: Yeah, we want to avoid the big words. What they wanted to know is: where is the most effective location for them to advertise at any given time? For example, how much should they spend in Germany or in Japan? They wanted to know how much they should bid for a particular ad word on Google at a given time. This scenario is equally relevant for a pharma company, an air purifier company, HVAC, cosmetics, automotive. Really, it can be quite cross-industry.
Ronit: Okay, but how can digital solve this?
Tamir: Ah, great question. You're getting the framework now, Ronit. Well, from a digital and data perspective, this company has a large data store of their historical sales. They know where they sell, they know their sales numbers, they know it by location down to longitude, latitude, zip code granularity. But the decision process on how to distribute their marketing spend is really very statically based on where they saw spend last year is where they'll spend this year. And they throw in a bit of stats on what they expect market growth to be. It's quite simple.
But they wanted to know more than that. They want to know where their customers are more likely to spend on a given day and in a given location. So they analyzed what other factors affect the buying trends of their customers? What other data is available?
They decided to evaluate environmental data to see if changes in weather, in pollution concentrations, or/and in pollen counts, could predict the buying patterns of their customers. They needed to identify a suitable technology following on from our framework. With such huge amounts of data, we're talking hundreds of gigabytes. They decided to use machine learning and regression analysis to search for correlations between sales and environmental conditions. So when they saw sales in a particular location did they also see that pollen counts or pollution were at particularly high or low levels?
Once these patterns were identified they rolled out a solution, taking these patterns and applying them to their advertising spend in real-time. For example, if the forecast, say, for New York, indicated the pollution and pollen counts were going to be at bad levels that historically showed that they resulted in higher sales, they knew that they would spend more advertising targeting New York prospects during this period of time, optimizing their marketing spend, going back to your question.
Ronit: Thanks for bringing it back for us.
Tamir: There are many other ways in which one can liberate the data in such a manner, taking historical data correlating it with external data, with internal data, and identifying areas for growth of sales, product improvement, and marketing planning. We've mentioned just a few of these here, it can go down to understanding pollen seasonality at particular locations or seeing how historical data trends correspond with local air quality and pollen levels.
And it doesn't have to be only in advertising. We're working with a smart medical company that's looking at historical patient records and correlating those with environmental variables to identify which types of patients are more susceptible to which types of pollutants. Now that is invaluable data for research and also for producing more personalized medicine.
So really there are a lot of areas in which you can take this to.
Ronit: I get it. I really do get it, and it makes it more clear. I'm gonna ask a question that I know that people are thinking to themselves. Is this only relevant to air quality products?
Tamir: Not necessarily. Of course, it's very clear the connection between companies who are focused on air quality type of products, be it in farming or smart home or automotive. But why should it be only air quality-related products? It's been shown that air quality affects people's moods. It’s been linked to depression, it's been linked to low worker productivity. So could this be affecting buyer behavior on any product?
Similar to how companies have been using weather and seasonal data for years already to predict consumer behavior and plan campaigns, pollution data is becoming a new input for predicting the buying patterns of all kinds of consumable products and financial instruments.
Ronit: Okay, so we all see the value of the framework and we see it in customer engagement and marketing and product research and in advertising, as we discussed previously. But what else?
Tamir: Okay. Let's take another example from the HVAC industry. HVAC is the heating, ventilation, and air conditioning. One of the customers we work with, a large residential and office ventilation firm, provides clean air to home and working environments. They wanted to improve the efficiency of their products and create a better quality of living and working for their customers, while also reducing the cost of energy utilized by their products. So this was their business goal.
Ronit: Okay. I've worked with this industry in the past, and to the best of my knowledge, you click a button when you want clean air and you switch off the system when it's not needed.
Tamir: That's true. I'm glad you're challenging me on this.
Tamir: Some of them also are doing much more sophisticated things. They're using sensors to gauge indoor air quality in order to automate the process and make it much smarter. So it's not just about clicking the button or switch on, switch off. They're using algorithms built into the control systems of air quality. When they looked at what digital could do for them, these companies understood that by connecting these controllers to a cloud solution, they could better feedback on their performance and improve the operations of the products remotely. An Internet of Things type of system.
They also realized, looking at available third-party data, that they could combine the data that their products produced with external data on forecast and real-time air quality, weather, pollen data, and create an even smarter ventilation system that will ensure to ventilate the inside air only when the air outside was cleaner. They could also utilize weather data to know when temperatures would be rising and pre-ventilated the room beforehand. As a result, they have significantly improved the quality of their products, helping to differentiate themselves from the competition, and also help to reduce the energy cost of their customers, a real win-win situation. In fact, a smart system such as this can take their experimentation into many other directions, such as the one in the example in the slide.
Ronit: Really addressing their customers' needs.
Tamir: Yeah. Finally, let's look at an example from a whole different industry: the automotive industry.
Ronit: Okay, this one's easy. The automotive industry is known to be highly polluting, and also super focused on digital.
Tamir: Yeah, exactly. So they're interested in pollution because they're known to be one of the biggest polluters, and so that's a big focus to them. But the other area that they're hugely focused on today is the health of their customers, the health of their passengers. What are their passengers being exposed to while they're driving? Many automotive companies have set a target, this is their business goal, to increase the health and maintain the health of their passengers. Let's take for example a company called Hella.
Hella is one of the largest automotive component suppliers. They produce climate control systems. They're a German company with over 20,000 employees.
Video Narrator: Since the invention of the first automobile, Hella has been engineering new ways to make your vehicle more efficient. Comfortable. Safe. But what if a car could do more? What if it could look after our health? Hella introduces the first cloud-integrated air quality management system for vehicles, powered by BreezoMeter. To work. To school. To the store. Add it all up, the average driver spends over 4 years of their life on the road, and long-term exposure to air pollution while driving can lead to serious health issues.
Using BreezoMeter’s accurate air quality data, Hella gives your vehicle access to extremely precise air quality information for any location in real-time. So it knows ambient air pollution levels where you are now, at your destination, and at every point along the way. Your air-aware vehicle can provide helpful recommendations and automatically take action to protect you, and your precious cargo. It all adds up to better health for millions of families.
Tamir: Ok, so hopefully you were able to hear that video, we have some feedback that some people weren't able to hear. But just a quick summary: basically, Hellas business goal is to improve the health of their customers and of car passengers, and they saw that by combining air quality data from outside, from a third-party, with their onboard car sensors, together with this air quality data, they were able to create a unique digital ecosystem around the car that improves their customers’ health.
So they take the data from their senses in number one, they send them to the BreezoMeter cloud, number two. Number three, BreezoMeter enhances that data and sends it back to the car to make automated decisions and inform the driver.
Basically, producing some clearly unique passenger experiences such as advice on when to open or close the window, or even automatically circulating air inside when you're driving through a polluted area, or the opposite, bringing in clean air when you know you're in a clean area. So, to summarize: if you focus on your business goal, in this case, a healthy car, and on liberating your unique data and mixing it with third-party data, you can maximize the potential of digital while avoiding the digital transformation hype.
Ronit: Thanks, Tamir. That was super interesting. Right before we cut to our Q&A, first of all, please feel free to start sending in your questions. We've left you with a takeaway, the digital solution framework’s questions that you should ask, feel free to reference it here, and as well when we send you the recording. And on that note I remind you again, we will be sending you the recording tomorrow in our follow-ups. And now onto our Q&A.
As they come to you feel free to send them. We have some coming in now, Tamir. Okay, here's one: this sounds like a framework that is meant for a more established product or business line. What if we're a start-up?
Tamir: Well, you know, we're a start-up ourselves, BreezoMeter, and I think this applies even more to startups because startups are always challenged with lots of ideas and limited resources so they’re forced to make harsh decisions. I think by focusing on the business and not necessarily on the coolest technology or feature that one of your customers has asked for but on the business goals, then you're more likely to maximize what you can get out of digital.
Ronit: Here's another one: we’re a lifestyle fitness app, can your data help us?
Tamir: Well, I could say that the cleanest route feature based on pollution exposure would be a great add-on to your app. However, that would be again putting technology ahead of identifying your business goals. So my question would be, what is the goal that you want to achieve? And I'd be happy to follow that up with you, maybe on a one-on-one call afterwards.
Ronit: Okay here's another one: I come from a company that is pretty traditional. They've hired us as a team meant to take the company digital but we frequently come up against blocks for a management board afraid of change. What's your advice here?
Tamir: Well I say stick to the framework. The board is not interested in your digital capabilities, they're interested in what business goal you're gonna advance. What problem are you gonna solve? So, find out what are their top priorities, and if you can connect your activities to one of those business goals, it'll hopefully help you to unblock. I see we've got another question here.
Ronit: I think this will be our last one. What different avenues does BreezoMeter use to gather air quality data? If there are no sensors in a given area how is data presented to the user?
Tamir: Okay, great question. It's a bit of a technical one but I'll explain. So, we're a big data company. We use any available data source that's out there, including environmental government monitoring stations. We use traffic data, we use data from satellites, we use weather data, and together we’re processing something close to 2 terabytes of data every hour so that we can pretty fairly accurately estimate what is the air quality in any location. We're using machine learning to gather that data and to help us make better estimates. The second part of your question is, how is the data presented to the user? We offer an API which is basically a programmatic hook, which allows you to pump your data into any sort of app and present it in any of the many ways that we showed during the demo here. Happy to take up and talk about that question further if you want to ping me separately.
Ronit: Great. Thank you so much, Tamir. I want to thank you guys for joining us, for participating in the webinar, for sending in your questions, for being here today, really, and, you know, keep on coming back to enjoy our content. I want to thank Tamir for being with us today, it was a really interesting webinar. And again, if we didn't get to your questions we'll follow up with you. And we will see you guys at the next webinar.
Tamir: Thanks, Ronit. Thanks for listening in.
Ronit: Bye, guys.