Adobe Analytics Tips and Tricks - May 2023 APAC Adobe Analytics Skill Exchange Grow Track

Transcript

Hi everyone, my name is Bhagis Patel and I’m delighted to have this wonderful opportunity to speak with you today. As a digital analytics expert, I’ll be sharing some of the insights on how underutilized existing features can be used to their full potential to maximize the opportunities. Originally from India, I moved to Australia 15 years ago and now live in Melbourne with my wife and our beautiful four-year-old daughter. In my free time, I love playing and watching sports like cricket, badminton and volleyball. My family and I enjoy traveling and going on long drives. At Coles, one of Australia’s largest and most iconic retailers, I lead the product analytics and insights team. Our team analyzes the customer friction points and support product teams in optimizing the customer journey on the website and the app, creating a product that provides a world-class digital experience to our customers. During my presentation today, I’ll share some of those learnings from our team as the tips and tricks that I hope will be helpful to you all. We’re going to cover four of those existing features, alerts, index page, global report suites and merchandising E-VAR. First thing I would like to talk about, an existing feature that is widely used, but often underutilized. I want to share with you how we started maximizing the benefit of this feature. And I’m talking about alerts, which are a great way to understand any movement within big and important metrics such as visits, orders, conversion rate and errors, etc. However, my first tip is to not limit alerts only for the high level metrics. You can set up the alerts for those insignificant but significant moments. These are the moments that might not be a big one, but they can still have an impact. For example, a specific error that may or may not have impact on large number of customers and their experiences. We have a similar example in our company for a specific scenario when a customer tried to secure a slot while having multiple tabs open. There was a bug that was sending hundreds of API calls for that particular user. It is a unique scenario, so you might not see a significant increase in overall API calls and for an IT team it might feel like insignificant thing. However, using error alerts could be a great way to pick up these sort of anomalies using a combination of multiple metrics and segments. Another way we are utilizing alerts is to monitor a bug that has been going around for a while, but you would like to be notified when it really start impacting higher than your acceptance level. We can also set an alert when a product team is going to release a new feature so you can understand and monitor the usage of that feature or even the availability of that feature. These were some of the examples where we have utilized for really small use cases. In today’s competitive market, speed is everything. Hourly granularity alerts can make a big difference in how fast we can react to those issues and stay ahead. I would 100% suggest to test it out and use it only for those specific metrics and not for everything. Once you set up the alerts, the next thing is to simplify the way you receive them. Setting up so many different alerts comes with the responsibility to monitor and take actions. An email might not provide the best workflow. So my tip is to simplify that workflow. We at Accoles have utilized a Slack channel for that. For those who might not know, there is no direct add-ons for Adobe Analytics in Slack. In short, Slack do have a feature called channel emails, which can be utilized to achieve this. What we have done is we created an anomaly alert channel and devoted all of our alerts into that email address, which then sends out a message into that individual Slack channel. You can also send some of those to an individual team or a squad if it’s really specific to them. What we then did is customize those email appearances for the look and feel like Adobe anomaly alerts, so that all the users can identify that these are the alerts that we are receiving from Adobe. The advantage of using Slack for alert monitoring are many. It is easy to monitor. All your notifications are going to be in one place for everyone. And then you don’t need to manage a distribution list. But the biggest one for us has been that it works like a thread. Every alert will be shared as a message in that Slack channel, so it’s easy to start conversation, escalate anything, investigate, fix any issues. Probably you can even raise a ticket directly from there. Finally, key to a successful alert monitoring is continuous refinement. I would suggest you should keep fine tuning the rules of that alert until you get to an ideal setting for each individual metric. You should identify and monitor the right audiences for the alerts that you are sending. A platform where you want to share all those alerts, along with what sort of granularity you want. Do you want to send out that hourly, daily, weekly? What sort of anomaly types you are looking for? Do you want to look at the anomalies that Adobe identifies itself? Is it going above, below? Do you want to specify any metrics there? And then the threshold for that individual metric as well. This will help you to stay on top of any issues. In conclusion, alerts can be a powerful tool in your monitoring arsenal, but they need to be set up correctly, easy workflow, and then monitored efficiently. On to the next topic, I would like to talk about how we can improve the accessibility and availability of data and analytics to solve some of our self-serve engagement within the organization. One of the biggest barriers that stakeholders face is finding the right workspace or the link that you have sent them about the self-serve dashboard that they requested some time ago. To overcome this, we have utilized a very simple Adobe feature called workspace as an index page. This has allowed us to consolidate all of our dashboard onto a one page. Then we were able to categorize those dashboards based on the channels, the teams, or even scored business unit, or even by customer journey. We were able to include a brief information about that dashboard to help users finding the right one for their individual question so that they don’t have to go through a number of dashboard and think about which dashboard is going to give me the answer to this question. You can also set up a progress status for each of the dashboard. So you don’t have to wait till the dashboard is fully completed and you can put progress or perfection. So you can have in progress status for that dashboard so people know that you’re still working on this one, but at the same time, they can utilize whatever has been done so far. You can also tag the dashboard as a new for a certain time period. So all of your team members can see that, oh, these are the new dashboard that we have included and they can start utilizing that as well. On top, on the index page, you can include the links to the other data sources and a dashboard that are outside of Adobe Analytics. It could be your offline data sitting in the Power BI dashboard or in a Tableau dashboard or completely external database, your own company BI tools. Additionally, you can include the documentation link, confluence pages, other data analytics related to content links and much more. Setting this page as a landing page for the entire team can significantly improve the engagement. Imagine about how easy it’s going to be to onboard a new team member, whether it’s part of the analytics team or wider external stakeholder team. Having the data accessible is only the first step. My personal tip on the top is to do a separate data literacy component to democratize analytics and data. We’re on the journey where we are running monthly analytics fundamental training sessions for everyone in our business. It is personalized to our business and the way we have set up our Adobe Analytics tracking for our own business. By doing this, we have seen a significant benefit for our entire team, including our product managers, business analysts, developers, designers, testers, who have all been able to self-serve analytics more often and take greater advantages of the hard work put in by our analytics team. In conclusion, this might seem really small, but it is a step towards creating a more data-driven culture within our organization and make more informed decisions. Moving on to the next topic, global report suites. A decision that we made at Coles a year and a half ago and the one that we have found to be incredibly beneficial. I know that many of you might be considering this option for your own business, so I thought it would be useful to share our experience with you. Firstly, there are a number of benefits of using global report suites. With careful planning and execution, it can provide significant advantages, especially if your company is on multiple websites and apps. At Coles, we have experienced some of those benefits since our implementation. To start with, consolidation of reporting. All of our digital KPIs, OKRs, the metrics that matters are available in a single report suite for all of our owned websites and the apps. This provides a clear view on how each of the websites and the apps are performing week-on-week, which also enables us for a clear cross-brand attribution within our business. Secondly, accurate reporting for overall numbers with a de-duplicated view. Now, we no longer need to roll up numbers every Monday morning or whenever our stakeholder needs it, it’s always de-duplicated. That de-duplication provides more confidence in the accuracy of our numbers. Most importantly, this has helped us significantly with our recent website migration. When we migrated our customers from one website to another one gradually over the period of a few months, the global report suite was a great way to track down those customers that we are migrating in segments, understand their performance, and compare against the rest of the similar group of customers. This has ensured that we can understand and keep an intact customer experience during the period of migration. There are definitely some other administrative benefits like simplified implementation, less error from the devs, time-saving, etc. But in summary, the global report suite has provided us with a host of benefits, and we believe it is an excellent decision for companies looking to streamline their reporting and improve accuracy. At last, merchandising e-vars. Have you ever wondered how customers are finding products in your retail e-commerce site? What are they looking at? How do they build their basket? And is that different depending on the pages, prices, or the promotion type they’re browsing? These are many important questions for any business looking to optimize their online customer experience. At Kohl’s, we have found using merchandising e-vars is a very powerful way to get answers to these questions and more. By combining different merchandising e-vars for product location, category, feature spot, search term, price promotions, and more, we have created over 30 different combinations that enable us to provide deep insights into product performance and category placement during the key events. For example, we can now understand how customers interact with specific product categories, which products are performing better in certain locations on the website, and how different types of promotions affect customer behavior. This information can then be used to improve customers’ product exploration as well as the basket building journey, resulting in a better overall shopping experience. In addition, I wanted to quickly touch on a few other topics that won’t be diving in today but are probably towards sharing. Some of the things that we are also working on and implemented is first-party ID stitching, which is a first step towards cookie deprecation. It helps us to understand the true first-time shoppers across our different channels and understand their behavior compared to our existing customers’ behavior. We have implemented search action rate, a calculated metric that we created to measure the effectiveness and performance of our site search. We created a metric called engaged versus less engaged visits as a replacement for bounce rate, which takes into account a combination of pages, time spent on the site, and events during that session. I would highly recommend and suggest to play around more and find more ways to improve and the utilization of tons of different existing features that Adobe has. I would like to sincerely thank you for listening. I hope you all have enjoyed it. Looking forward to any questions that you might have at the end. Thank you.

Hi, everyone. Welcome to the Experience Makers, the skill exchange for Adobe Analytics. Thanks to Adobe for having me here. Today my topic is create a healthy momentum for digital analytics in your organization. A little bit about myself first. I’m Victoria from NAB. I’m senior consultant on digital channel analytics. I’m the product owner for a few Martech products and Adobe Analytics is one of them. My focus is to help our business get the most out of the investment on those products and achieve business outcomes. Besides that, I’m also focused on adapting digital analytics solutions for the cookie less future. Outside of work, something interesting about me is I have a master’s degree in chemical engineering and I used to be a food editor back in uni that I used to be paid to eat. I enjoy traveling and water sports. I have a Labrador named Mocha who I paddleboard and kayaki with during summer all the time. So my story with Adobe goes a long way back. Starting from Adobe Experience Manager, I slowly got my hands dirty across the whole Adobe Experience Cloud, including analytics, campaign, target, and audience manager. In terms of my favorite product, as you may already guess, it’s Adobe Analytics for sure. I was one of the three global finalists in Adobe Experience Maker analyzer category back in 2020 and last year I finally won the Experience Maker of the Year award. And you can see my proud face directly from Adobe’s website. I have been on there as the cover girl for the past 12 months and I can’t wait for the next winner to be announced in two months time. So you’ll be able to finally see a new face there. I have experience across different organizations and different industries. Some need to establish digital analytics implementation from scratch. I took over an old implementation that requires completely redesign. From those experiences, I can share many success stories, but I also witnessed many bad practices. I’ve summarized my experience based on all of that and I’m happy to share below key learnings with you today. They include four key components in digital analytics practice, data strategy, governance, knowledge democratization, monitoring mechanism, and review and audit cycle. Before we dive into details, I want to ask everyone on this call, what do we want to achieve with Adobe Analytics or with any digital analytics products? We want to track and understand user behavior so we can gain insights. We want to measure the effectiveness of our marketing campaigns. We want to identify areas of our digital assets that needs improvements or optimization. And ultimately, we hope business can take real actions based on the insights derived from all of the data collected by our digital analytics implementation. But before we can achieve all of that, there are some solid foundations we need to build first. We need to have a comprehensive data strategy. What do we want to track? How we’re going to track it? We’ll also need governance, setting up disciplines on how and when we document things. And we can’t just set up and tracking and leave it behind. We need to constantly monitoring and make sure our tagging and data quality are in good state. After all of that, hopefully we can finally reach our wonderland, actionable insights. When people will be able to make business decisions based on the insights we generated from Adobe Analytics. Let’s start with data strategy. I’m sure everyone on this call would agree the importance of a solid data strategy before we rush into the tracking implementation plan, pause, and really work out your analytics strategy. Data strategy exercise can take weeks, and it shouldn’t just be discussed within your digital analytics team in solo. Invite marketing team, sales team, anything that will benefit from digital analytics. Brainstorm together. Capture the great business goals, KPIs. You’ll also be identifying your data sources. Will you be unifying the website, app, social, and CIM data together? Mark this. Also discuss and establish your data governance practices during the discussion. Below are the common are-os I witnessed in my past experience when people rush into analytics implementation without thinking through the strategy first. You’ll see KPIs not captured in the analytics implementation plan, wasted time and resources on collecting data that isn’t actionable. Not taking the entire customer journey into consideration. Web and app properties are isolated and cannot be combined to understand the overall performance. What even worse is it may violate privacy regulations. PI got collected in custom dimensions or URLs. Every business is different, but there’s still some templates we can use to help us shaping a good data strategy foundation. If you’re ever taking a project to implement Adobe Analytics from scratch, you should already know a business requirement document, also known as BRD, is the start of everything. It’s a place for documenting all of your desired KPIs, reporting requirements, and any data point you wish to see when your Adobe Analytics implementation is complete. Ask yourself, what are the things we want to track on our site? What data points will be important to me in reporting use? And most importantly, how will those data points inform decisions? It is important to ensure each of your business requirements related to data point that can be used to inform business decisions. It can be tempting to want to track every click on your website, but at the end of the day, what’s the actual insights are you getting from that reporting? That’s when the Moscow method will be handy. Categorize all of your requirements into must have, should have, could have, and won’t have.

Don’t rush when working on BRD. Take time to engage with your stakeholders and brainstorm together. The worst thing would be tracking everything, but nothing would lead to any business decision, no matter how fancy your dashboard is, it’s no value if no one is making decisions based on it. After a comprehensive business requirement document, next step will be implementation. The implementation itself was a whole separate session. And today I want to focus more on the governance documentation and knowledge sharing part. It’s often deprioritized and even non-exists in some organizations. We left a huge hole in the analytics practice and often lead to the failure of the analytics team. Governance is a key part of building trust out of your analytics strategy. Governance is the mode to protect the accuracy, consistency, compliance, and accountability of your data. Bad practice in this will damage analytics teams credibility and break trust. Common goals I see in these areas are incomplete, outdated, incorrect documents on analytics. Key resource left and rest of the team only has incomplete knowledge on analytics implementation. Marketing team don’t understand how tracking works and developer team don’t know what correct answers mean. So let’s talk about documentation. Documentation isn’t sexy, not by a long shot. But it’s absolutely critical for getting the most out of your analytics investment. Yet we often see it overlooked, deprioritized, or even non-exists. Ask yourself this. Do you or someone in your organization have a solid understanding of exactly how your data is being populated into Adobe Analytics? If you bring a new analyst onto your team or someone leaves, what are you going to do with all the knowledge of the custom side of your implementation? If something breaks and it will, trust me, are you able to fix it? And even more important question is almost always overlooked. Do you know why you’re capturing what you are capturing and how you can use it within the tool? Any observations should be documented. If it is confirmed there’s a data issue, document it as soon as possible. Chances are your documentation is lacking and a solid variable map or solution design document can go a long way to help answer some of these questions and get your analytics programs back on track. It should list every variable in use by report suits along with all relevant details for the variable setting. How the variable is implemented and what its purpose is in reporting. For anyone new to implementation, this document gives the best view of all variables implemented and what their purpose is so individuals can self-serve in terms of learning your Adobe Analytics setup. It’s non-negotiable that this needs to be a living document. If you added or deleted a variable, document it as soon as possible. What comes hand in hand with a good documentation is a good monitoring mechanism. It can be one of the worst nightmares for analysts to discover data issue months after the issue started. What’s even worse is people may have been self-serving and made decisions based on the incorrect data. Frequently check your data accuracy and look for unusual signs in reportings. Analysts should take an extra step to learn the technical aspects of tracking so they can better sense problems and raise smart questions for the technical team when the data looks suspicious or incomplete. For data monitoring, Adobe Analytics already offers some automation that we can utilize directly. Alerts can be one of my top five loved features within Adobe Analytics. You can start with simple metrics to be monitored. Simple things like traffic spike alerts, set up alerts to you and the team whenever there’s a sudden increase in traffic to a website, which could be an indication of a successful marketing campaign or an unexpected viral post. This will allow you quickly respond and capitalize on opportunity. Or, bounce rate alerts. Set up alerts to notify you when a specific page or section of your website has a high bounce rate indicating that users are not engaging or the page is broken. This will allow you to investigate the issue quickly. You should also monitor technical issues such as website downtime or errors. You may even be aware of a 501 issue way ahead of the dev team. And of course, set up alerts for your conversion goals and KPIs. If there’s a major drop, alerts buy you time to investigate and respond at the earliest notice. Adobe Analytics Health dashboard is the other tool I use now and then. It has been there for almost a decade. It can be a little bit slow and took a few minutes to run a full report and I personally don’t use it on a daily basis. But I found monthly to be a very good frequency or after every major release. It gave you a quick view of how all the metrics dimensions are performing. In short, as a pre-built health dashboard, it comes very handy. If you would really prefer it to be real-time, you can recreate your own health dashboard in the workspace. Which takes less time to refresh your reports and also you can customize it to suit your own needs. We are now at the final topic. Review and audit. While tools like alerts and health dashboard help monitoring the performance from a technical perspective. On top of that, we should also cautiously set up time to review and audit our analytics practice from insights and business value perspective. Ask yourself below question and set up the review and audit cycle based on your responses. Do you spend more time reporting data than analyzing it? Do you never get any feedback from your stakeholders on your analytics reports? Do you have time to do any ad hoc analysis or testing? Do you have everything you need to derive actionable insights for your business? Review your level of engagement with your stakeholders. This will probably be in the most critical step of building a healthy momentum of digital analytics. Most of the time it’s even more important than the technical side of analytics. Ask your team, is your data quality good enough? Do your stakeholders agree that digital analytics is not nice to have and it’s a non-negotiable requirement? Is your analytics documentation up to date? Have you conducted enough training and skill sharing sessions to wider teams? Do your stakeholders reach out for insights rather than reports? And do they take action from the insights you derived? If there’s more no than yes, you should probably action now. Reach out and seek feedback from your stakeholder directly. How can you make analytics more valuable for your stakeholders? So it’s almost the end of my presentation. Here’s a quick summary of everything we have discussed. Start with a clear understanding of the business goals and objectives. Set up effective measurement frameworks. Review your business requirements and analytics implementation regularly. Set up your analytics monitoring mechanism. Document everything. Build a data-driven culture. Review your level of engagement with your stakeholders every now and then. And continuously iterate and improve. Digital analytics is a non-negotiable and ongoing process. And it’s important to continuously iterate and improve your approach over time. This will involve regularly reviewing your data insights, testing new approaches, and making adjustments based on what you learn. With that, that comes the end of my presentation. Good luck, everyone. I wish you all the best with your digital analytics endeavors.

Bhagwesh and Victoria, thank you both for being here. Thank you for having us. Lovely to see you, Akshay. Thank you. How are you, Bhagwesh? Likewise, same. Thank you so much for having us. All right. Now let’s dive into some questions. The first question goes for Bhagwesh. Does the audience want to know, can we actually make a report for alerts in Adobe Analytics? You know, something like for the alerts that gets triggered, it gets into the report? I think actually that’s one of the questions that I wondered so many times as well. So from my knowledge, it’s something which is not possible and it has some limitations from the Adobe side, actually. But obviously, you can actually dig in within the Adobe, the League pages, the document pages or the past Experience Maker sessions to see if that is possible. I have always utilized the alerts page actually to monitor that. What are the alerts I’m sending in? And then I think the use case for the alert is to make sure that you only get it actually when you need to. So probably that could be one of the reasons that there isn’t any report that you need to monitor yourself. Likewise, the alert can get sent to your inbox or your Slack message directly. Got it. For the next question to Victoria. Victoria, how can an organization create a culture that supports and values digital analytics? You know, many times like it is pretty hard to for the teams to actually work in an environment like where digital analytics is not valued. So like what kind of culture would you recommend so that digital analytics is able to make an impact on the business and is able to, you know, really create a niche for itself? Yeah, thank you actually. That’s a really good and big question, and I’m glad someone raised this. I know like both myself and Bagesh talked a lot about the technical side and the practical side of Adobe Analytics today. But actually to make digital analytics successfully in an organization like building a culture that actually supports and braids digital analytics is actually the foundation to achieve success. So for me, the organizations I observed that gain success, first of all, it needs to be starting from the very top. So the both the top down support and encourage individuals and teams for data driven decisioning. And also, I have observed like the teams and organizations which provide sufficient fundings, trainings and resource for the team to build data literacy among employees, and also to encourage and recognize individuals and teams that actually made good decisions based on the data. So that’s, I think, some good observations I observed in organizations that actually successful in digital analytics, implementation and practice. Back to you. Thank you. All right, thank you, Victoria. My next question is for Bagesh. Bagesh already wants to know, you know, that the bounce rate in Adobe Analytics, will it be updated to match GA4 new bounce rate definition? You know, that is for any visit, which is 10 seconds or more will not be counted as bounce, even if like there are no clicks that has happening. So how will there be an update to Adobe Analytics to match it with GA4? Thank you, Akshay. I think that is a great question. The one way I’ve looked at is that the Adobe gives us the capability to create the calculated metric. That means it doesn’t require Adobe to change the definition. You can create your own metrics the way you want. So the way we have took on the bounce rate as the existing definition only looks at the single page visit. However, what we have done actually that we have tried to match along what we need. So if the GA4 is doing more than 10 seconds, you can actually set yourself or you can define your own bounce rate to match against the GA4 if that is the requirement from your business. So I would say don’t limit, just use that calculated metrics and create whatever it would need to be. Thank you.

Thanks, Bhagesh. I think that’s what I like about Adobe Analytics. It actually provides you all that flexibility to, you know, if we want to actually create some kind of a metric, the calculated metrics is the way to go. I think, Bhagesh, I would again bother you with another question that I’m getting. How do you access index pages? Oh, okay. That’s a great question because what we have seen over the years is there are a lot of existing things that people don’t know. We come to know about these ones through Experience League, to the community chats within the Adobe or the documentation within the Adobe. My answer to that question is that the index page is not an existing feature. It is an existing workspace that you can use as an index page. So you open up any workspace that you would normally do, utilize the features within that workspace. For example, you can create multiple panels, you can resize those panels, you can set that as a landing page for every single user or the set of user that you would like to. And then you can actually put it as a read-only format so they don’t see any other panel within that page. That makes them feel like this is their index page, actually. So it’s just an existing workspace. Explore. Thank you.

Okay. Victoria, next question for you. This is one of my favorite questions. How do you measure if stakeholders in an organization are actively utilizing analytics in their decision making? While we have seen, particularly when I go and meet customers who have Adobe Analytics, the leadership or the senior stakeholders, they are interested in understanding, is my team actually leveraging the capabilities of Adobe Analytics? And not just capabilities from a user’s perspective, but from a perspective of making decisions which can impact business. So how can this be orchestrated and how to know about whether that’s happening? Yeah, that’s a really, really good question, actually. So for me, I hope it didn’t get categorized as stalking, but actually Adobe Analytics has a feature called logs. In the logs, you can actually see who is actually using analytics, like logging, using reports. So sometimes I will take a look at the logs and understand, is my stakeholders actually looking at the reports I created for them? Or is it only a set and forget? So if I notice someone is not utilizing it, I will actively reach out and understand like, like, is there anything actually we can improve? Is the reporting actually helping you? And so that’s something technical. You can see whether the user is using the report. But more importantly, the other way to measure it is actually you can tell whether if you are leading an analytics team, you can tell whether the stakeholders will invite your team to their key decision meetings. Are they actually seeking advice or your team is actually running in solo, like basically a reporting machine? So the worst thing happened to analytics team is become a reporting machine without providing insights. And the best model I have seen among so many different organizations is actually to embed analysts in the score. So they are centralized analytics team, but embed different specialists in different scores, like product scores or delivery scores. So they can actually contribute and also provide insights, advices, doing the delivery and product shaping process. And that’s the best. You shouldn’t be only like analytics only provide data and reports and certain goals, always the insights as the goal of digital analytics.

Thanks, thanks, Victoria, for answering that pretty insightful question for Bhagesh. Bhagesh, can streamlining streaming APIs can be used to grab raw data to trigger real time custom alerts from backend, rather than waiting for alerts from Adobe analytics? I think actually that’s one of the things that we’ve been testing for a few times as well.

I would say explore more into that zone. But the main question here is that how much of an investment you want to do actually, because Adobe has an existing feature called alerts, that is very simple to set up, easy to use actually without complicating too much. So if it’s a daily alert, if it’s a monthly alert, then you wouldn’t need to set those sort of an API, the raw data send that you would need to trigger anything from the raw data. But I would say if the organization has sort of a capability or the investment that you would like to make, to make it more real time, you can definitely explore.

Okay, okay. And I know like, we are just running out of time. But I really wanted to ask each one of you, you know, like if you can actually take a provider share some kind of a key takeaway for the audience today, you know, that would be brilliant.

If I can start, I think my one key takeaway is to explore and test more things actually, because Adobe has a lot more to offer. The documentation is extensive. So just try and utilize that as much as you can.

Thank you, Bhagesh. I think for me, actually, I want everyone to work away with something not that sexy, it’s about the importance of documentation. I’ve seen many organizations suffer from PEE, Analytics Resource, leaving organization, and no one is actually can pick in the knowledge up. So documentation, documentation, documentation, I cannot emphasize that enough. Do good documentation of your analytics implementation and business requirements. And good luck with all your analytics endeavors.

Thanks. Thanks, Bhagesh. And thanks, Victoria, for these wonderful insights and the golden nuggets that you have just shared.