[Music] [Sean Robinson] Good morning, everybody. Thank you so much for joining us. I'm Sean Robinson. I'm the Program Manager for the Adobe Analytics Champion program.
We made it, the last day of Summit. I hope you've all had a lot of fun the last few days. If your feet are hurting like mine or your ears are ringing after Bash last night, so glad to see you're still here. We've saved some of the best for last with the Skill Exchange.
Today, I'm going to be introducing Isha Gupta, the Digital Analytics Lead of Three Ireland. Isha's going to be talking about Transforming Digital Channels in Adobe Analytics. She's going to be talking for about 45 minutes, then we're going to have about 15 minutes of Q&A. We'll have mic runners coming around, so start thinking of your questions as Isha is presenting. But please join me in welcoming up Isha. [Isha Gupta] Good morning. Thank you everyone for coming. I really did not expect many people to come after the Bash last night, but here we are. So I'll just start with a quick introduction about myself. So my name is Isha Gupta, as Sean already mentioned. And I am Leading Digital Analytics practice for Three Ireland since October 2022. I am two times Adobe Analytics champion 2023 to present, which is the proudest accomplishment of my life till now. I am passionate about CX strategies, and, of course, please feel free to connect with me on LinkedIn to know more about me. And that is a picture of my son and my husband who was just waiting two hotels down for me because they wanted to come along. So the Session Objective for today, so I will just start by discussing a bit about the three different channels that we have for customer interaction through which a customer can interact with the brand and place an order or basically just convert because conversions are relative to different industry. So we have online channel, which is favorite of this audience, which includes digital websites, mobile apps. Then we have offline channels, which have in-store buy-ins where users can just go and buy something they like. Then we have hybrid, where you can just place an order online and then just collect it, something like click and collect. Now our focus for today is going to be-- Forget about offline and hybrid, we are just going to look at how we can maximize our return of investment on our digital channels. So it's all being done to keep make your head of digital a happy person.
So what we will learn today? So for this, I will just start discussing with the problem and what I'm proposing and what is the value potential of this. So the problem is that globally, marketers and analysts alike, like me, have the strategies expectations on them that you need to deliver strategies that increase the digital channels ROI, but as well as your customer experiences should not suffer at all and they should actually get better with time. Now what I'm proposing is I am going to talk about five strategies that have worked for my business that using which we can create some impactful and actionable segments in Adobe Analytics that can drive margin, ROI, and as well as give you deeper insights into your customer CX. The value potential is that we can increase the ROI on our digital asset. So for example, your Adobe Analytics is a huge investment. Right? We have to justify the cost as well as we need to increase the realizable business value on our digital investment. So to do that, as the first thing, let's bring our customers into the perspective because in this day and age, as per studies, more than 67% of your customers will leave you if you just give them one bad interaction. Also, I would assume all the empty chairs are representing the customers right now, so I'm happy to have more customers.
Also, just bit of a disclaimer that I will be talking with the lens of fictional businesses, none of which are true, and I really struggle hard to find five names that do not exist. So all the data, all the facts and stats that are going to be represented are fictional. They are not real. Okay? So let's dive into our very first strategy that is digital leakage prevention for which we are going to do revenue optimization from digital journeys.
So the very first business that we are going to talk about is 7ish Telecom. Now funny story, I am from Three. I tried to look for a number, something like six or seven or three or two, something that will just resonate with that. I was not able to find a single number. Every number was taken as a brand, so I just came up with something like 7ish. So 7ish is a Telecom provider, and they sell phones, prepaid SIM plans across their websites and their mobile applications. Now if we just take a typical day in the life of a 7ish customer, the customer goes to the landing page, they add the product to the cart, they goes to the checkout page, they go to review details page. Now from here, a conversion is supposed to happen and they're supposed to purchase, but that does not happen because it is 7-ish. So the customer fails to complete the purchase within the digital channel and the customer ends up escalating to call center. Now this is the point of digital leakage. So digital leakage is there is the point where the customers start where basically customers abandon your digital journey, and they start their journey within the contact center. So this is something that users can complete the task within the unassisted channel, but they're moving to assisted channel. Now you may say a sale actually happened. So how is that a bad thing for business? Well, let's take a look through some numbers. The hidden cost of digital leakage. So the prevalence of digital leakage is such that 88% of multichannel journeys will escalate to contact center when digital solutions fail, 38% of Gen Z and millennials will abandon their journeys if their digital solutions are not sufficient. And, of course, there is a particular cost associated with each call that goes to call center, which lies anywhere between $2 to $5 per call, 72% of customers expect to receive instant responses from digital channels, and 64 customers are willing to pay and pay more and complete their journeys if their issues are resolved within the same channels. And I think that makes up for all of us. Right? We don't want to hassle of starting in one channel, then we have to call into the call center. We just want our conversion or whatever action we are doing to be completed within the same channel, and that's all of the customers. So my proposal is that we can use Adobe Analytics to identify friction points that are driving users from these unassisted channels to assisted channels. So some steps that we can do is, so first when we can identify high traffic pages that are leading customers to customer care contact and we can create a segment of unique visitors who are spending above average time on the high contact pages, and then we can just use that segment for our deeper analysis. We can also pinpoint high call trigger events. So simple thing, you just identify what is that event which is most prevalent before a customer started a call care interaction. So that can be a login error that could be a user is not able to complete the registration or they're not able to-- They're having payment errors. So all of these little things, these little errors are very important for us to understand why customers are not able to do what they're trying to do. Then we can also use Adobe Analytics plugins. So there is a plugin called as Time Between Events, which we can use to count average journey times from start to finish, and then we can just use it to-- We can couple that with the first point to see what are the pages where users are-- What are the journeys where users are spending more than average time? And then we can provide help instantly.
We can also detect drop-off points in conversion funnel by looking at where are the points, where are the pages, or basically, what are the last pages from where the call interaction start. So some example of segments. So for example, this is all sample data that I've taken from the sandbox account. So here you can see that these are top five pages. And if I look to the chat initiates event with that, I can see that the web login page is the page that is driving maximum users to call center. Or basically, they're just asking the user to start a contact with the call center. Now you can just create a segment of something like visitor. Now about the segments, they are really just about to give you a rough idea of what you can do, and it will really, really depend so much about your industry. Another example which probably you can use to get deeper insight into your system is login issue. For example, a user who is getting more than two login issues and then they are doing a call initiate, so what is the impacted volume of visitors through that? So these are some of the things that we can do. Now let's see what 7ish built these segments and what did they achieve through this. First and foremost, they fixed the most frequent errors that were impacting the most users. They introduced video support for complex journeys, which is basically if you are not able to complete a journey online, just have some additional support for that. There is AI help chat popup that automatically popup whenever the time lapse between journeys was more than average. They also provided assistance to make users complete journeys within the same channel. And also, this is very important, that they increase the feedback on the type of device that user is using to complete the transaction. If it is a mobile, then, for example, the forms in mobile look very different from forms in website. So if it is that, then the feedback changed accordingly. What it achieved for 7ish was they saw 10% reduction in call volume that saved them $0.2 million in revenue annually and also it increased their digital channel conversions. Now the key message that I would want you to take from here is that we need to prevent digital leakage to propel digital conversions.
So with that, we will go to the next one, which is Loyalty Unlocked. How can we turn our customers into ambassadors? So this is one of my favorite, which I am really pushing hard for my company to pursue. They are trying to do it, but, yeah, it's a good one. So before starting that, I will just ask a question. So have you ever left a good review for a brand that you are loyal to? For example, if you're using the same telephone operator for last five years, have you ever left them a good review? Jen have. Okay. I haven't. And I'm sure most of us haven't, which makes sense. Right? We did not get any incentives for that. So let's again go back to our fictional business. Now our fictional business is Bufferflix, where loading never ends. So it's a streaming based platform where you can stream, buffer, load, binge, and eventually able to watch content. So how long-time customers of Bufferflix are feeling? First, they do not feel valued. They do not feel rewarded. Loyal customers are at a risk of churn, and customers who have negative experiences are leaving bad reviews, but loyal ones are doing nothing. So business is missing huge opportunities in cross-sell, upsell, referrals, and sales for their loyal customers. So why loyalty is so important for digital growth? Because loyalty rewards leads to higher retention, which in turn leads to increased lifetime value of the customer and in turn you have the boosted digital revenue. Also, the impact of loyalty engagement on revenue growth is exponential in such that there are studies to support that loyal customers spend 67% more than new customers. Not only that, the importance of loyal behaviors is that top 10% of most loyal customers spend three times more per purchase than remaining 90% customers. Now we see that loyalty is hard earned but often underutilized. For your business revenue, 65% of the business revenue comes from your repeat customers, only 35% comes from your new customers. So all these studies, like you can see the sources, this is as per Forbes data. Now what if I tell you that we can make our loyal customers as our brand advocates, we can ask them to become our best marketers.
So for that, we are going to go back to Adobe Analytics to identify what are my loyal behaviors. So the audience criteria here would be, first and foremost, we need to identify what identifies exists for my industry. For example, I am from a telecom industry, so we have CTN, which is call to number. It could be email address or just the ECID. Now the important things about identifiers that they need to be properly hashed before bringing into the system as well has your DPO approval attached to it. And, of course, depends per industry what you're going to take. The second step is going to be that we have to track accrued revenue, audio conversion metrics. So for some e-commerce, it's straightforward. You have to have your orders, number of orders, revenue, but it will depend on different industries. Then you just filter your high value propositions, like whether that is top orders, but corresponds to loyal behavior as your industry. So these are some of the industries where you can see loyalty behaviors across different industries. For example, for streaming, it would be watch hours, and your Adobe Analytics dimension would be your user IDs, subscriptions. Hospitality, it would be rewards number, fitness membership ID for telecommunications again, and the loyal behavior will account for what each industry what it means for each industry for a customer to be loyal.
So the example segment, so this one is actually pretty straightforward, all you need to do you just look at your visitor level and you just look at your conversion criteria and there is also a dimension in Adobe Analytics out of the box which we will see later, it's called as customer loyalty. So you can also use that to just see loyal customers.
So this is again some sample data. So you can see for user identifier, these are the hashed identifiers, and this is the revenue. So for example, these are top 15 users who have spent more than 2,000 Euros. So you just need to take those users. Now if you want to target users through their email addresses, just take the data from Adobe Analytics and you clash it with your CRM system, and then you have their identifiers to personalize them. Now how Bufferflix rewarded loyal customers was, first and foremost, they provided coupon and loyalty benefits to top 100 users. They boosted the referral program. So I think most of the businesses have a referral program. So for the loyal customers, they provided the offer that if you are going to offer for some time, then we will give you 2X rewards. They provided extra benefit on the social handle promotion. So this actually impacts the customer influence value. So what your customers talk about your brand, the word-of-mouth, and also the organic content that really, really matters for others. If I'm being told by you, if you recommend me, then because I know you are a customer, I would probably trust you more than somebody who is directly coming from the brand. So the other thing, they also asked for reviews in exchange of lucky draw, something that we haven't been asked before that's why we never left a review for our telecom operators. So what it did for Bufferflix was that they increased their customer acquisition...
They gave them their user-generated content, organic user-generated increased two times. They have plus 30% positive reviews, and the loyal customers started using their discount coupons. Now that also increase their customer influence value, their customer lifetime value, so that actually has a good-- And also customer knowledge value. So the customer knowledge value comes from the reviews. So it says you just have to ask for honest reviews. Now the feedback and the reviews that your loyal customers can give you can greatly give you the potential to increase your features of your product itself. So that customer knowledge value is very important. So the key message here is that investing in loyalty is a revenue multiplier.
So that brings us to the third one, which is High Engagement Low Conversion Targeting. Now this one is favorite of my boss, so he really liked that one. So this is potential unlocking of your best prospects. So let's take a look at our third business, which is Styfie, and let's see what was the problem with Styfie and how they handled it. First, Styfie is an online clothing and fashion store, so they sell everything on sale. They have sales mostly, but the problem is that their potential customers visit, but they leave without converting, and they're not staying.
Their high potential users who have high potential to convert, they are-- So their marketing strategies are pretty generic basically, so that means their high potential customers do not feel like it's connecting to them and they are just leaving unengaged, 67% of their potential buyers, they are just abandoning the journey, so they are starting, they are supposed to complete, but they don't feel like they should complete it. Now the objective is that Styfie wants to convert their frequent visitors into frequent customers. So they don't have low or zero conversion rates, but they want them to. So what Styfie did, before that, I think we will just take a look at this question. So I do that. I don't know how many of you do that. So if you visit a brand website, for example, if you want to buy a perfume from a new website, you visit them and instantly there will be a popup that will probably say, "Subscribe to our newsletter," and you will get-- New customers get 10% off. And I think most of the brands have this. For new customers, they have some sort of campaigns running. So my question to you is that how many of you wait for a personalized offer promotions before converting on a brand for the first time? It's great. Right? Because we all do that. Right? So now let's take a look at how conversion timing is important across various industries. So the average visit to conversion ratios across various industries, if you take a look at that. So for an e-com, basic e-com, for a new customer, it takes around three to five visits to convert. For something complex like B2B, it takes around 7 to 13 visits to convert. For travel and hospitality, customers take around three to eight visits to complete. And for high value goods, for example, if it is a car or real estate or something more complex, it takes anywhere around 10 plus visits to convert. Now the factors that affect the conversion timing, first and foremost, urgency. So your limited time discounts. So for example, Amazon frequently has Big Billion Days. There are Cyber Monday, Black Friday. So these are the urgency-- They create a sense of urgency in users that it is a limited time deal and you have to grab it. So even if you don't need something, you probably just stack up all the stuff.
The product complexity also affects it. So for example, if you are going to look for a new headset or new headphones for your office device, then you have to look at what is the ANC ratio and how it compares to the other devices because there is just a lot of devices that are available in the market. So that complexity adds to the research time and also time to convert. Trust building is also very important. If it is a new brand, which you haven't really heard of, you will definitely take longer time to convert. So you have to have multiple interactions to build a brand. And also because there are so many scams that are live these days, we need to know that this is a brand we can trust and we can purchase from. And also channel influence, so how your marketing activities are performing, how you represent your brand in the social media, how your retargeting campaigns are performing, that really impacts how soon your customers will convert on you for the first time.
So to identify high engagement and low conversion behaviors in Adobe Analytics, we can essentially look at different types of behaviors. So if we just think objectively across our different industries, I believe everyone here belongs to different industries. So for you, what will be the high engagement? For example, for me, it would be users who are repeatedly viewing the bill pay, prepaid plans, they are clicking on the upgrade buttons, but eventually they are not converting. So some examples would be High Product Page Engagement where users are repeatedly visiting the product pages. They are spending lot of time browsing your products, but they are not converting. And some Adobe Analytics metrics to track here would be product views, average time spent and page views. Also, frequent use of search features. So you have, I think most of us have the search feature. So if users are frequently searching for some item, but they are exiting from the search page, so that means that users are interested in your products. Users are looking to take further action, but probably they are looking for some promotional offer, and they are not converting. So there you will look for internal searches, exit rates from search pages, search terms, etcetera.
For promotion page-- And also there is promotion pages, like you have frequent promotions and you would like to see users who are frequently engaging with promotional offers, but they're not taking any offers. So you can just take a look at banner click-through rates, your product landing page visits, promotional landing bounce rates, that's actually an important one. And, of course, multiple visits without conversion, like users are coming, they are visiting you for the multiple times, but they are not converting.
So the segments that Styfie created for user behavior metrics that corresponds to high engagement without conversions work. So they looked at on a visitor level again, they looked at product views, visits, cart additions that exist in a certain amount. Your product views and visits exists greater than five. That's just a simple segment. Right? But for them the order does not exist.
Another segment that was more specific to the behavior, their internal searches, product clicks, visits exist, which has greater than 5, greater than 10 or something, but again, the conversions do not exist. So what Styfie was able to achieve with the Adobe Analytics segments? They were able to launch some personalized recommendations for their premium products for their frequently visiting customers. They were able to show them high value loyalty benefits, so they were able to show them that we have this great loyalty program, convert with us, you get this VIP membership offers, they showed them exit intent popups with lucrative offers when users were going to leave. They showed them the upsell, cross-sell bundle offers whenever the user visited next time.
To incite a sense of urgency, they started the limited-time discount codes and also offered free trials. And they also showed them personalized feature bundles with low cost. Now something else that they were able to achieve with these segments were, they were able to also understand the deeper insights into the customer journeys, why their users are not converting? What are the friction points that are keeping users from converting? What are the behaviors of the most frequent customers? Can they group similar traits of the different customers? And these customers know about promotions at all, do their promotions have that sort of awareness or not? So with these segments and this analysis, Styfie was able to achieve 27% increase in digital conversions, 20% reduction in cart abandonment and 15% lower acquisition cost, which was really good for them. So the key message here is that quality of our traffic is more important than quantity of our traffic. So what we need to do is we just need to focus on keeping a high-value customers who are highly engaged with that and focus on converting them.
So with that we are on a fourth strategy, which is Churn Prevention Campaigns for establishing strong customer relationships.
So to start begin with, let's just take an example of understanding churn. So let's say you are throwing an epic party with good food, music, party, snack, and everything. But after an hour or so your friends start leaving you saying, "Hey, it's not you, it's the vibe and I'm off from here." So that's customer churn, when customers decide to stop using your product or brand and they decide to ghost your brand like you're a bad business party. So the quirky-- Let's just take a Quirky Challenge of Churn. So what QuirkyCart is doing right now? So QuirkyCart is an online marketplace for all things weird and wonderful like that Groot shaped mug you will see or something weird. So, the analyst of QuirkyCart saw that their loyal customers have just stopped showing up anymore. They are not coming in and they are showing signs of disengagement. Now what Quirky wants to do, they want their customers to come back, they want to retain their customers and they want to prevent churn. Now to do that, let's just take a look at why should we really care so much to prevent churn? Now before start that there was something I read very recently and that really resonated with me that we all talk about customer lifetime value, but do we talk about the customers' 7 day, 14 day, 30 day value? I think this is something that we need to start taking a look at because acquiring new customers is anyway five to seven times much more costlier than retaining the old ones. Your customers, if we just boost our customer retention by 5% that has the potential of increasing our profits anywhere between 20 to 95%, which is massive. So I think we should really value the customers that we already have and we should really work on keeping them. So again, question, so how many of you have ghosted a brand because something better came along? Okay. We all do that. So let's see how we can identify churn using Adobe Analytics. So for that, we can build inactivity score, so we can just look at what your declining engagement signals are. Now that could be reduced time spent on-site, fewer logins, fewer visits, fewer page views, and that again is very relevant to the industry that you belong to. Some examples of identifying inactivity signal metrics in Adobe Analytics would be, past customers who used to be there, but they have stopped engaging, no engagement in last 60 days. Reduced page views or session duration compared to their average. Cart additions without purchase in the last 30 days. No active logins in last 60 days. Now about the active login, a colleague of mine told me a very interesting thing that if a customer is going to switch from, let's say, they're looking to change their telecom provider, they will not actively log in, but they will probably just log in once or twice towards the end just to see if their contract is about to expire or when is the date of their contract expiring. So then you know that if a customer is coming very, very less logging and it's not an active login, so they're not engaging. They're just coming to see, "Okay, this is my last contact date," and disappearing. That means your customers are about to churn. And also less than three visits in three months, which is, I think basic. So along with this, Adobe Analytics has this excellent resource cohort table for giving you retention and churn rates. Now this table, it is so feature-rich, you can just look at by dimensions and there are so many retention rates, churn rates, and I think it deserves the skill action on its own, so I will not go into the details of cohort table. So what QuirkyCart did to build segments using Adobe Analytics? So they use the customer loyalty dimension. So this customer loyalty dimension has four possible values, which is not a customer, which is zero purchase, then new customers, one purchase, first, then it is new customers, then it is loyal customers, which is anywhere greater than three purchases. So it's a very, very good dimension. It is out of the box. Just use it. You will see what is the percentage of your customers that are loyal to you, but in the last 60 days or you can just remove the data range from here altogether and you can just use it to see that these users have less visits, less logins, and less orders. And other thing that you can just see that an order exists, but then within two months or a stipulated duration, the order do not exist again. That means users are not coming back. So how QuirkyCart targeted customers to prevent churn? They send them targeted win-back emails by saying that these are personalized product recommendations, special discounts, loyalty points for you for renewed engagement. They also send them reengagement incentives. For example, if you are back to us, there are some three months of subscription that we are giving you, free shipping, we are giving you.
When the users were not on their website, when they were across different channels, they send them the retargeting ads, display ad, marketing campaigns to bring them back to their site. And when customers were on their site, they showed them on-site display campaigns to make them convert again. For example, just again, free shipping, some higher incentives and discounts for when they return. So what it achieved for QuirkyCart, they were able to lower their churn rates by 15%. They were able to increase the reactivation of disengaged customers by 7%, which actually overall increased their digital channel revenue share by 5%, which is actually good.
So the key message for this strategy is that churn prevention is the key for building strong customer relationships, fostering digital channels growth.
That brings us to a last one, which is propensity based segmentation for capitalizing convertible behaviors. So let's take a look at Specktular, which is our online smart glasses selling platform and they're encountering few blurry spots in their conversion funnel. So the problem is that their acquisition costs are skyrocketing, their funnel conversion rates are not skyrocketing, they are just going down, and their generic marketing is not resonating with the customers and customers are just not converting. Most of their customers are leaving without buying. They have very high final drop off rate. So what Specktular wants to do, they want to identify those customers that are most likely to convert and only convert them because they also want to reduce their acquisition costs. So the solution is that we can use propensity-based segmentation.
So what it means is that you just identify the users who are not converted right now, but they exhibit similar behaviors to your high-value customers. So these corresponds to-- It's essentially a three-step process where first you will define a high-value criteria to identify factors that corresponds to high-value customers per industry. So now again, it will depend per industry that, whether that's orders, whether that's subscriptions or travel. So what becomes high value to you? You have to identify that high-value criteria, then you have to map that high-value criteria with your Adobe Analytics metrics, and then you cluster your pre-conversion behaviors. So users who have converted and users who are providing you brand high value, just look at the pre-conversion and even post-conversion behaviors to see what is the overall-- For example, what are the downloads that they are focusing on? What are the pages that they most frequently view? Do they look at your how to guides and everything? Then you cluster those behaviors and you identify the customers who exhibit same behaviors but without conversion. Now all that's left is to personalize and measure impact, so you deliver your personalized content, sales offers, early access discounts, and targeted banners to promote products or services for those users who you think have the most propensity to convert.
So how you can segment convertible behaviors in Adobe Analytics? So for this, there are some key behaviors that we can track. For example, Asset Consumption. So again, what are the key downloads? What are the newsletter subscriptions? What are the videos users are viewing? So take it as-- For example, if I'm looking to convert on a brand or-- I want to, but I'm just not converting for the first time. I would probably be looking at the manuals, how to guides, what the product can do to me.
I would probably be looking to watch videos. So all these behaviors corresponds to customers who are highly interested in your brand. Then you can also track Product Views, your product page views, views to your how to guides, your FAQ sections, and your form interactions that users who are visiting your Contact Us form or other forms, callback forms, but they are not converting. You can also look at users who are adding a product to the cart. They are in the consideration phase, but they have not yet converted. You can also look at the users who are spending more than average time on your key pages. Now an example segment here would be that you look at download ID, for example, this is just a sample asset that this asset corresponds to a high-value behavior for you, so just see that this download exists for this customer but online orders do not exist. So what Specktular did to convert their convertible traffic? They were able to engage users who had a high propensity to convert by showing them dynamic offers. So they started showing them dynamic banners wherever they went. Like, there are smart glasses that are restocking soon. They also send them personalized email to show them that if you're still thinking about those smart glasses, here is additional 10% off. They showed them exclusive offers, VIP discounts to propel them towards conversion, and they also shown them live chat nudges. So when users were on their pages, they know that these are-- The customers who have high propensity to convert, just show them the nudges. Are you struggling to check out? What is it that you are-- Is there a problem can we help you out with? And what Specktular was able to achieve through data-driven targeting, they were able to get higher conversion retention and revenue rates with 27% increase in conversion, 20% reduction in cart abandonment, 15% lower acquisition cost, which was very important for them and 20% increase in repeat purchases. So this overall increased their sales and customer acquisition, which is what we get from data-driven targeting. So the key message here is that we don't need more traffic, we just need to convert right people with the right message at the right time. So that's very similar to that you just need to focus on the quality of traffic and not just the quantity of traffic. And I know that the buzzes that get more-- We all launch campaigns to just bring more visitors in. And I think our campers are very much focused on, whether or not we were able to bring, let's say, 100 users to the website. But I think the focus should be that out of those 100, how many were actually converting, how many became your loyal customers, how many were able to provide some value, in terms of customer knowledge value, customer influence value. And I think that's what we should target more.
So, in summary, I'll just summarize the five strategies that we discussed. So the very first strategy that we discussed was Preventing Digital Leakage, where we can reduce interactions with assisted channels by timely targeting our users, which has an increased cost savings. You can reward loyalty of your customers to implement strategies to turn your loyal customers into your brand ambassadors. So it's actually a good one. You can just give them some incentives to promote your brand, that will increase your brand advocacy. Then, High Engagement Low Conversion, which will identify and nurture your engaged users. Basically, it will convert your frequent visitors to frequent customers and just have a high-value customers. So it will increase your acquisition and adoption. Churn Prevention, where you can build and activate win-back segments to Adobe Analytics segments. And this overall will increase your customer loyalty. And then we just discussed Propensity Based Targeting, where you can use Adobe Analytics to find users who have the high propensity to convert, so this will impact your revenue directly.
So, the key takeaway here, to implement any of these strategies, I think the step we need to take is, first, we need to identify our goal. So this strategy or even if you want to come up with your own, the first and foremost thing that we need to do is, we need to identify what is the business KPI that is most important to us, what is your business KPI that gives you the maximum ROI on your digital infrastructure. Then you map that KPI with your Adobe Analytics data. So this is something that you just find out that if orders matter to you then, of course, it's straightforward order, but if more complex systems, for example, B2B, it's lead generation. So you have to identify which lead generation matters to you, and you just map your metrics to the KPIs that are available in Adobe Analytics, then you create your segments and audiences. Then you analyze and personalize. You use those segments to analyze the behaviors of your users to drive insights, and you just see how best you can target and personalize your users, and there are many strategies to do that. And, of course, there are different systems that will allow you to do that. Now the most important things, measure the wins. So for this one, and I think for data nerds, like I'm hoping most of us are in this room. I think we all do the hard work of coming up with strategies, crunching the numbers, getting something implemented. And if you present the numbers, it gets overlooked. They probably don't care that you were able to come up a solution out of thin air, all they care about is numbers. So I think it's very important that we represent our wins in a business speakable format. We need to be able to communicate our values in terms that directly relates to the business values and gives you the leverage that we are doing a value addition. And I think the senior executives probably do not care as much about, but went behind that. All they care about is what was the measurable result. So we have to focus a lot on, what is the win that we can measure and present it. And then, of course, if you are able to do all that, I would say that you will have happy customers that are happy to give you five star reviews, but more importantly, you will have a happier head of digital.
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Also, go check out Experience League. It's a place to get personal learning content, build your skills, network, get technical support. Go to ExperienceLeague.adobe.com.
Isha mentioned her user group, but user groups are a place for customers to network with other customers. They're all customer run. You can problem solve. You can share ideas, best practices, technical learnings, and get more education. And finally, we are going to be opening our applications for the Champion program in a couple months. This is a group of who Adobe recognizes as some of the best practitioners in the world. If you're interested in applying, please do. Also, if you're interested in just talking to one of the champions, we would love to connect you with somebody to work with you on some projects you're working on. If you have any questions, scan the QR code and we can connect you. We are going to take about a 30-minute break. We'll be back in at 10:30 for the next sessions. Hope to see you there. Thank you everybody, and have a good one.
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