Hello everybody and welcome to another SearchStar webinar the third in a series of webinars were hosting this week the whole week is dedicated to conversion analytics that’s because all of us here know how important this topic is without it all other digital activity would be completely meaningless okay so that’s a bit of an exaggeration but you get the idea and today our focus is on the analytics part to present it we have a brilliant double act we have our lead analytics consultant Jon who’s joined by a client of ours, Connor from Pure Planet and they are going to explain how we’ve worked together to improve the tracking through the online user journey we also have another analytics consultant from the team Chris who’s going to talk through a quick analytics case study afterwards. Now lots of you know who SearchStar are but please be patient for a minute because for those that don’t I’m just going to talk through that explanation so we’re a digital media buying agency with expertise in getting the most out of the world’s biggest advertising platforms Facebook Google Amazon and many more and we do this internationally and in multiple languages and we also have a brilliant team that focus on analytics and conversion and it’s on these two areas analytics in conversion that we’re focusing on with the webinars across the course of this week these two areas are clearly big topics to cover and this slide gives an indication of all the different things that we do to improve clients websites performance the important thing to remember is it again the best impact the biggest impact we start on the left and make our way across the right to start with we need to examine the data to understand what is happening on a website before we seek to understand why or what to do about it and so today we’re coming back right to the start to the far left of this slide and in John and Conners talk you’ll see the importance of getting your analytics set up brilliantly and what that means to reinforce this further one of our takeaways that we’re giving away a part this week is an analytic scorecard these are the two scorecards that you can request from us the analytics one is essentially a list of the key things to check in your Google Analytics set up a landing page one is a framework to help you objectively review your own landing pages it’s a starting point to help you do that so please do get in touch if you’re interested in receiving either of those a quick reminder of what’s on across the course this week this program is available to download in the right hand side of your screens on under the handout section you should be able to see a PDF that you can click on Monday’s talk from Harry and yesterday’s talk from the guys that use oolitic s– are available now on youtubes so go to youtube and search for search though or check out our social channels where we posted and shared them there and you can see those lots of people are already watching those in addition to the people we’ve had on the webinars themselves i’ve mentioned today’s focus is on analytics and that’s what’s coming up tomorrow we have Jamie Wilmot from pure electric he’ll be giving us a client-side perspective on conversion optimization and on top of that each day we’re doing a quick 2 minute case study after the main talk the culmination of all of that is that we’ll be finishing on Friday with a broad discussion few people being invited back to join a panel where we’ll discuss if he themes of the week and so far based on the questions coming through have been shared with us and in during the webinars it looks as though our key areas of discussion they’re going to be on these sorts of themes so things like what are the best cro tools to use what are we going to do and cookies are no longer around some specific points about what I should which what should I consider on a non ecommerce website so we can come back to some of these points and we’ll cover them off on Friday there’s still time for you to change the main topics that we’ll be talking about on Friday so keep your questions coming in and make sure that if you’ve got something you think’s a hot topic we should be talking about send it through now that just the last few bits before I hand over to Vaughn and Connor remember to share tell us what you’re up to if you’re sat in the garden watching today in this beautiful sunshine then make sure you share a picture from from that wonderful location we’re all stuck inside as you can see but hash tag search tower 20 I’ve mentioned all the recordings that are available so each day will release the recording from the previous day and then we’ll release the collection of recordings next week please send us your questions through there’s a questions widget in the GoToWebinar panel on the right you can tweet us at search underscore star and ask questions via Twitter or you can send any questions on email hello at search – starker tuk that’s the same address for where you can request one of the school cards and then after all of our events we send through a post event survey please please give us your

feedback we really really appreciate it what we do is we help incentivize that we send out we will pull a name out the Hat of the people that have completed it and we’ll put one person and we’ll donate 200 pounds to a charity of their choice and finally we’ve not got any specific events lined up with particular dates or content agreed exactly yet which is a strange position for us to be in because no one we’ve got loads of stuff coming up but we’re taking a bit of a breather and we have got some stuff that we’re discussing about what we’re going to do later than you it’s got some great ideas that we will share that via our email newsletter and also on our social platforms so keep an eye out for those because they’ll be coming through very soon but with that I will hand over to John and Connor who will now go through the main talker today they received John okay I love our seamless this goes cool okay so hi I’m John I’m the lead analytics consultant at search start so this this webinar is going to be a collaboration between myself and pure planets data scientist Connor got us I’m going to be looking at what searched I did to help your planet better understand their website user journey and how we used ecommerce tracking on what is not an e-commerce website Connors then going to look at what pure planet did with the newly collected data and how the data from GA is just one source that they work with so start with pure planet in search star we’ve worked together for the past 18 months like really bizarrely I having never heard of pure planet I signed up as a pure planet customer and then less than a week later before they’d even switch my energy they contacted us about some analytics work it also means because I’m a customer I’m now never allowed to leave them so yeah that’s unfortunate so at 16 we we learned by him the opportunity to try new things and from the start of our relationship your planet have allowed us to push the boundaries of the GA set up and try things that we think are cool which we really enjoy being able to kind of like trialed these new things one thing to venture I’m going to be controlling the slide transition so whilst I can do this during doing my side of the talk when it gets to Connors just remember it’s gonna be my fault and not his so we’ll start I let Connor introduce himself and pure planet thanks John um hi everyone what a wonderful sunny Wednesday it is for everyone to join us today so thank you for coming along yeah so as John said I work for pure planets we’re a digital renewable energy supplier based in the beautiful city of Bath as it happens actually just a stone’s throw away from the search start off assists which works out really well it means we’d get out the office when we were meeting pure planet launched three years ago now and in that time has really grown rapidly and accelerators so we as I said we’re a renewable energy supplier for UK domestic homes so anybody in the UK is able to go to our website get a quote for their energy and switch to us and we guaranteed to provide 100% renewable electricity and a hundred percent carbon offset gas to your home we offer a range of fixed and variable types the the introduction of the fixed tariffs actually is very new it was launched about a month ago and what helps the sets apart is our zero markup on our on our energy cross so the price that you pay for your unit rate with your planet is the price that we paid to to supply your property we’re able to do that as a business model because of our fully digital approach so we don’t have any poor sensors or any large massive teams if you need any help or support then you’re able to do that through our AI chatbot that we’ve aptly called watt and then either he’ll be able help you or you’ll be passed through to one of our Member Services team and this I have this approach of working in a super lean and efficient manner allows us to save money and of course that means that we’re able to pass those savings on to onto customers we were really pleased as well to be awarded a which recommended energy supplier for 29th a student for 2020 and we were also featured in the Sunday Times track once to watch of 2019 as well so it’s been a bit of cracking few years for us cool thank you so the brief that we got from from pure planet the website surely was really simple okay a visitor would use the website to get a quote and then once you got a quote you would download an android or iOS app and complete your switch and pure planet wanted to get a

better understanding of the user journey ok well the problems that we kind of faced with it is that it was a single page application so essentially what that means is that it’s a single URL and there’s no page change in between so the only visibility that if your planet had initially was the the count of users who started the process and the count of users who finished there was nothing kind of in between so during the quote process no personal information was requested so there was no way to tie up the user who kind of initially got a quote and then went on to kind of get the switch so this made attribution kind of really difficult and the only goals that pure planet could optimized their media towards were soft kind of goals such as quote completion as app downloads so rather than actually kind of the tangible switches that they want to optimize towards so our approach so shortly after we started working with your planet luckily for us the quote journey became a quote on switch so users then had the ability to switch online after they’ve received their quote what this did this made the quote and switch journey a ten step process rather than the five step of the original journey it also meant that it was no longer frictionless because the user had to give personal details when they were switching it’s what we did using a combination of event tracking and custom dimensions we added tracking on both the the quote complete and the switch confirmation page so that we knew elements such as the fuel type energy usage the postcode area and journey type sort of in Google six you can’t collect any personally identifiable information and this does include code so instead what we decided to do is capture the first part of the postcode so for me it would be BA – and this is actually a lot more useful because for capturing each individual users postcode you know when you’re looking at a report what you’re seeing is just you know hundreds and thousands of individual post codes but by grouping ins of individual areas there’s obviously going to be a lot less numbers we felt that this information was not maybe might not be immediately kind of useful right now we felt that in the future it could help to inform the kind of media activity for the above-the-line activity because we’ll be able to know exactly who has initially asked for a quote but not then gone on to switch and a journey type was really important because um they actually the quote and switch journey was just one of three journeys that existed on the website the other journeys were like a moving journey so if you were an existing if you moved into a house that already had a pure planet as the energy provider and the journey was obviously very different and the way that you’ve moved through was very different and on top of that there was a journey that they called the pcw a price comparison website journey and very little of this journey actually took place on a pure planet website but the users still had to visit and visit it to confirm that they’ve switched so what we were able to do is separate those three journeys to look at performance and we used virtually URLs because even though the user only saw one you know specific URL within GA we tracked each one as a separate page and we felt it was important to kind of track this information both and the quote complete and the switch complete because at the quote stage if you use a DIN switch then that information could be used to kind of customize the remarketing efforts and if you use a had switch by having this information we could look at what elements of the media activity had been most effective and then pure planet would be able to update those accordingly the biggest change was around the steps was around tracking the steps the user journey so in previous talks that we’ve done I’ve spoken about our love for using enhanced e-commerce tracking for non e-commerce journeys and the main reason is because of this this one visualization that you get the checkout step so normally the checkout step is here as it sounds it’s the steps of an individual checkout but essentially any kind of you know core journey can be tracked in this same way you know the great thing about these types of journeys is you get the visibility as to who moves from one step to the next and where they drop out and where your planet it was just it was a really great journey to because it’s so rigid you know there’s the ten steps of the you know getting the quote and then going on to switching with enhanced e-commerce you can only have one of these checkout funnels so you know we focused on the core quote and switch journey we didn’t focus on the move in or the pcw journey you know if we wanted to track multiple journeys then we might you know might like to do that using goal funnels which you know kind of do the same thing but it’s not you know it’s not as visually clear as this journey because with the you know the enhanced e-commerce tracking we’re essentially creating a transaction in terms of a transaction value what we did is just use an arbitrary value of one we did we did have discussions with your planet about using things like custom and lifetime value but because the price of energy kind of goes up and down we felt that it might kind of become misleading and what we didn’t want to do is kind of have misleading numbers in the data because we wanted pure planet to kind of have confidence the numbers that they’re seeing and all of this was all built using Google tag manager using just kind of basic custom JavaScript to create essentially that ecommerce funnel that we’d normally be added using data layers by a developer one thing interesting was we did this we discovered there’s actually an eight step limit to a checkout funnel and so we couldn’t track the entire ten steps with your planet which is again the first time we never discovered this was a limitation of it so what we did is we actually started you can see on the Left I quote complete and that was because

the the first part of the journey was so frictionless knowing from no personal information was asked for it has such a high conversion rate we thought actually we’ll start from the quote complete because the obvious you know there’s gonna be obviously a very big drop-off from quote complete between that when they used to then start or decides to start to the press which process and so before I kind of hand over to got to go to Connor the the GA enhancements that we made provided kind of a really clear separation over those three journeys that a new user might take and the performance of each one we gain visibility over the choices that a user would make during the journey so each of the options that they had to make we captured that information we also added tracking so that it was immediately clear where any pinch points might exist and we enabled the media activity to be optimized to two macro rather than those micro conversions so we can actually you know target when you use I had given across that information when they have decided to kind of switch over to pure planet okay now over to Connor cool thanks John so yeah so what my what I’m what I’m basically try and do is to is to give everybody here a bit of a bit of a wider background to how we take in and use the data the searched are have helped us to quite using GA and using things like the advanced e-commerce and bring those in to our data stack with impure planning and then also how my self in the deck science team in collaboration with our sales and marketing teams I’ve been able to use stuff to use this data to make changes to to this funnel to allow us to you know get a better performing overall acquisitions process on the website so just to kind of give people a bit of an understanding I mean about how acquisitions work with your planet so as a prospective customer and John has already alluded to this in a couple of this points a prospective customer actually switched their energy supply to pure planet in in one of three different ways so firstly they can sign up to us directly by our app or our website and it daddy’s by far the quickest and easiest way to switch their energy supply to peel planet and we refer to that as our direct channel because obviously a customer is directly interacting with us in order to to initiate a switch there secondly we allow existing customers or we provide a mechanism through which existing customers to recommend us to their friends and family through a rewards based system that we call member get member so this operates in a very similar way to to other brands where you can refer a new you know a friend or family member to peer planet and we will reward you and the new customer fall for doing that and so that helps to build brands add vacations and sort of awareness across our member base then thirdly we like the vast majority of energy companies in the UK also allow people to switch to us by our affiliates such as price comparison websites and clearly with today’s market around difficult comparison sites and you know a large array of energy providers it’s a very competitive market and allowing missed by being on this price comparison sites we’re able to get a wider brand reached and we would just be able to do on our own as a you know as a small but lean energy supplier what so when we started working with suits are about 18 months ago there was a lot of focus at our time internally on really wanting to sort of hone in and double down on making sure that our direction also our app and web funnel was working as far as it possibly could for us and we wanted to see if there was anything that we could do from a day of science and analytics perspective that would help us as a business to identify any areas of that funnel that may not be performing so well or any of anything else that we could do to help bolster the contribution of that direct broken switch journey that John was mentioning before across our webinar towards our overall acquisitions so taking this as a business objective of wanting to increase joins from our own direct channel I started working with the with our marketing teams to really break this down into a set of smaller action lists and these action lists would contribute back up to hopefully delivering this overall objective and each of these

action lists have their own set of targets their own set of KPIs and measures that we want to use to assess how successful we being and achieving those different sort of areas and ideas once we so in the case of of this objective we were really looking at driving traffic more traffic to the website making it making us more visible across you know across the various other platform working on juni conversion and making sure that that conversion was as high as possible throughout the quotient switch funnel and make that as seamless as we could and then finally utilizing the data that we could obtain and that we already had obviously in a responsible way and adhering to to users privacy preferences to allow us to bolster our marketing activity effectiveness re activity effectiveness by being able to to target groups and different with different characteristics so once we had these action lists we were able to convert those over into a set of requirements that we would need from from the data and this is where then search style really really came in to help us so we took those requirements and we converted those into into what we ended up calling data capabilities which you can see on the right hand side there and these capabilities have a hierarchical structure to them which made it really easy for us to figure out with John and his team what the priorities and timelines are going to be in spoons are the different dates for climates we had for GA so we started we needed to start with that with a kind of measure layer which was figuring out what we want to measure while a telemetry is nothing moves to an understanding phase and reporting and then finally we moved into an optimization stage and I’ll cover those more in a second so starting off with the with the measure phase the first priority for us really was to identify what telemetry we already had in GA because we GA was already set up when we started the project but it’s I think it’s fair to say that we only really had the very bare essentials in there and really only default reporting that you kind of get anybody gets when you sign up with Google Analytics and the unique nature of both our produce which sort of funnel and also John was mentioned before about the unique way that others our website is built other single-page ajax sort of developed web application made a lot of that default out of the box reporting you know tricky tricky to understand and actually not particularly useful to us it gave us numbers but they were really numbers that we should then relate back and then communicate that’s the business so once once we identified that this is basically what we’ve got in G at the moment isn’t isn’t gonna work we then started working very closely with John and his team to identify okay what do we need to do in GA in terms of building those analytics metrics out in order to make this something that we can use so we’re moving from the starting blocks though that you see in the bottom left of the diagram where they’re not very complexed just overall you set up but they’re actually not very useful and very quickly we were able to identify some quick wins for us that allowed us to very quickly begin to get more use out of the day so without actually buying a lot of additional setup so for us that was using things like custom channel groupings in GA that allow us to map different traffic sources to channels that make sense to us up your planet so a good example of that would be traffic from a member get member stream so we were able to identify traffic that previously would have been labeled incorrectly using the default traffic reports and channel groupings and we were able to realign those two that match the unique channels that exist within your planet and clearly that then helps us to identify the compute the contribution of that channel and those other channels hat and then secondly really basic stuff actually just making sure that we had UTM tabs on all of our links so being a hundred percent digital all of our communication is done by email primarily or chat as well but but most of this is through email and obviously we have advertising digital advertising as well and so making sure that we had UTM tags on everything again helped us dramatically to understand where our traffic is coming from to the website and then as you know over the course of a few of a few months we we sort of evolved those things are and then we started to think about okay how are we actually going to get the most value out of our GA and this is where again John and his expertise really came in and they were able to help us decide on on

custom events and custom dimensions that we should build into GA that allow us to capture rich quantities quantitative metrics cific to our use cases that we could then feed into downstream segmentation so that would be things like identifying different people what so identifying different sessions as they move down the funnel by things like their their energy usage that they’ve selected by whether their gas or gas and electric by the postcode area and you know those are things that meet you then use to help give us a better profile of what what the general shape of people who are coming down the funnel really look like with all this stuff as well we had to find a sweet spot in terms of the data resolution and we had to think really hard about what do we actually want to know about the website about the performance without an Mitchell that we’re not just adding data for the sake of adding data and that’s something that actually is really easy to do you you can sort of go down a route of really wanting to put everything in and throw the kitchen sink at it but the reality is a lot of that you probably won’t really end up using and it just muddies the water and clearly again we you know we wanted to make sure that we were keeping data collection to the barest minimum even though in GA everything is anonymous it’s just not in our nature as a pure planet to want to start collecting stuff unless if we can really prove that the case for it so John mentioned earlier about the e-commerce funnel and the enhanced e-commerce funnel and once this was in place we actually started to see benefits almost immediately and a really good example there I’m obviously welcome anyone to go to the website and have a go at just getting that quote because you can start to understand the kind of probe what the process looks like but but basically in order to generate a quote we have to know a bare minimum sort of set of information about you or about all your energy supply and one of those is your energy usage now originally when we first set up the enhanced e-commerce model we we have two different paths that the user can take when we asked them for their energy usage the first is that we have asked them to give us their actual readings from a previous bill or previous annual statement and though that of course allows us to generate the most accurate quote for that for that household but we appreciate of course that not everyone has that two hands and so we also provided the optional still do provide the option for people to kind of select a high medium or low bounding based on either rough energy usage or by cost per month and originally when we initially launched the e-commerce funnel we presented the users that the user on the site with the with the actual usage in cuts first so we asked someone to enter their actual usage but rather than asking somebody initially whether you want to choose high medium or low and arguably one is one of those is easier to do than the other and what we actually found is that by having by presenting the actual the the question what are your actual inputs your actual usage inputs first we actually saw a drop-off in conversion or after that point and we couldn’t really we initially sort of found that really interesting and so one of the things that we did we talked about it internally and one of the things that we did we actually decided but that I don’t that diverting those two diverting pass phrase of friction point so it also says well what what would happen then if we swapped those two rounds so rather than asking somebody to enter their actual usage first what what would happen if instead we said look you can give us a best guess but if you’d like to give us your actual readings then you can go and do that and you do that over here so both doctors are still available but we just swapped the order in which we presented those options and what we actually found was by doing that once we made that change on the site almost immediately that conversion rate from that point onwards increased by quite away and you know had we not had though that telemetry we just would not have known that with with our previous self so that was really neat and you know nice example of using that data to make a change and interventional to the website and then use that for for for the betterment of the overall performance and it also proved to our business stakeholders the kind of return on investment that they could get by investing in doing this type of work around the analytic space so once we’d

sort of focused on the on the measurement side we moved so John well that’s up the next slide thank you so yeah once removed once we sort of obtained all this or this new fancy data in GL the shinier it was you know as the data science team it’s our job to really try and take that raw data and expose that in a way so our business stakeholders that makes that consumable and allows people who have a lot more domain knowledge than we do to be undertaking insights from that and you know as a business Google Analytics and on our web analytics that is incredibly important to us but actually it’s only a very small part of our overall of the overall signals that we’re getting in terms of understanding what our customers are doing what our websites doing and panels working so what we what we’ve been building internally is we’ve been engineering a brand new data stack and this is a very traditional data stack if you google this you’ll probably find something very similar to this diagram where basically what we what we were doing is we were taking all of these different signals all of our different systems that power our business so obviously GA is one of those but we’ve got Salesforce which is our customer relational management software and we’ve got all our ad platforms and our email platforms and what we basically built was a system that ingested all of those securely through our set of ETL pipelines and we were able to to deliver that into our internal data warehouse so what that basically delivers to us is is a way of having data from one district system like GA and combine that in you know immediately with data from a completely dissing other– disparate system like Salesforce or Facebook hats and clearly as you know that allows opens up immense opportunities for us in terms of bridging this this air gap that we found to exist between sort of GA cookie based analytics or you know upper funnel measurements and combine that with Salesforce data and sort of bottom of funnel and conversion measurements and of course we could also bring in by Brillion in our ad data we were able to begin to combine the ads the the data about how our ads are performing and where they’re really best and again combine that with GA to understand okay which ads and which particular creatives of particular ads are delivering the best performance in terms of different conversions so you bringing this data into one single place that reaches scrutinized unmailed in any way we see to Seafarer really open the door to you know to allowing us to begin as the data side seems to begin to expose this data back how to those business stakeholders that ultimately were going to make the decisions about what we did move forward nests like jong-kul thank you so I forgive me the slide is a little bit blurry but basically what I wanted to try and do is just to give a very brief indication of how we’ve used this in terms of exposing this data from g8 back out to our end users in the business so pure plan I already had an existing business intelligence tool kit and it made a lot more sense for us to bring the GA data into that existing VI toolset that all of our users and all my colleagues were already familiar with rather than trying to get everyone to understand how the Geo UI which I tried and failed a few times on that and so this is this is an example of where we were able to bring that geo data unify in the data warehouse we can build new tables that take different data from this from different sources and bring those together to create new analytics and reporting tables that we are then able to expose graphically by by RBI tooling and this is where our end users like our marketing team and our management team our tech team are able to look at those metrics and combine those with as I say all these different other sources for Salesforce and Cenred and the like and it really gives you that line of sight between all these

different systems and that was really be the breaking point for us in terms of beginnings really make proper uses of data and also more importantly get everyone else at the business excited about the data as well and get them understanding that they can use these metrics to make real decisions that are going to reflect the bottom line because before it was all just numbers and now they were able to really see it and digest it for themselves so a measurement we have our understanding and in the final planner that was really the I guess the most interesting part for me personally and looking at our optimization so sorry so yeah so we took we were doing from measuring and reporting through to taking real action and what we actually started to do and again searched are have been instrumental in helping us with this we wanted to use this data in order to empower teams within within the business to be able to make intuitive improvements very similar to those that we don’t improve on with the energy usage example I gave you earlier so what we actually do is we have this sort of cycle of measure test and deploy and again this is nothing groundbreaking this is you know this is very well sighted as a as a good way of coming up with a strategy for how to deploy these and make these iterative improvements but the the important thing here that I want to stress is if you look at the diagram in every one of those three areas measure test and deploy marketing sit within them and that’s really important because what this what having all the states are and having all these reporting in RB isil enables was it allowed the marketing themselves to drive those improvements and because they were empowered and they had the data to hand in a way that they should digest so they should you looked at the measurements that we were collecting from GA and all our other sources and understand what maybe isn’t working next they could use tools like google optimized which again searched our helps us to set up and get working to in collaboration with with my team to understand okay and decide on what do we what do we think is happening what do we think should be happening and how are we going to test for that and so we used google optimized to help us build these experiments and these a/b tests and meet you then use optimize then run those tests and assess them and then finally once we were happy with them you know and if we found any particular experiment to give a much more favorable result compared to what we currently have or has we could then immediately deploy those to the website you with with assistance as a tech team in order to you know reap the benefits from from those improvements that we were able to make you know immediately but as I say the key headline here is is that once people have the data and they understand it and they can use it you know everything else trying to just Falls Artful carries on from that really so that was a real eye-opener for us to have the marketing team driving all of this activity right the way through the iterative cycle the penultimate thing I just wanted to talk about them was personalizing ad experiences so again this is another another thing that we were able to do off the back of having all this amazingly rich qualitative tech I was just wanted data inside of GA and one of those was to be able to create dynamic audiences within GA that we could use to categorize and group together different different users based on their behavior so for example we could group people together by people who have say completed quotes and selected a higher youth energy usage banding or instead we should we drew people by saying okay get me everybody who has started a switch that hasn’t yet finished and again you know as an alternative we should say okay actually get me a group of everybody who has gone right way through the process and and have finished a switch and once we had all these different you know very specific audience lists built within GA we can export those to our advertising and email marketing platforms to be able to really begin to build much more creative much more engaging and experiences because we knew more about those individuals we still didn’t know anything uniquely identifiable about

them but we knew about their behavior and so that allowed us to create these these audience lists within of each of those different destination platforms that allow us to build more engaging arts and hopefully leading to higher conversion across those ads because the ads make more sense they’re more relevant to you they’re not just sort of sprayed everywhere for anybody to see regardless of actually how far you bought you have like how much you know about a planet or how far through that web switch Jun you got so that was that was a really powerful tool as well that we can all utilize and then finally the the most I think this is so this is probably the most exciting thing for me in my role as the data scientist but really what we’ve been able to do as a combination of all of the activity that I and the approaches that I’ve mentioned up until now and the only merging research start to get the data into GA but also taking that data and unifying it with all our other data sources into in our in our warehouse has been to be able to give us the opportunity to evolve our approach to modeling the attribution of the different conversion paths that people can take between you know first and never hearing about pure planet through to see in their first ad through to getting a quote and then going away and coming back right the way through to finally switching and this in particular we we’re still working on this this isn’t a finished project by any stretch but what we starting to be able to do is build out our ability to attribute conversions along what are often very complex and sometimes fragmented marketing journeys you know as I just said it’s very rare for someone to click on an ad on Facebook and immediately converts there’s that there’s a lot of stuff that happens in between and by having the this higher level of telemetry in GA and combining that with the Facebook from Salesforce and other sources we were able to go from these one-hour very what I often quite simplistic single touch or multi-touch attribution models that are supported within GA and not not saying that these aren’t useful because they absolutely are but for our particular use case they didn’t really eat me any of those models didn’t really represent the full reality for us of what we knew our customers were we’re going through in terms of that conversion process and that’s really important knowing that is really important because without it’s very very difficult if not impossible to be able to attribute sorry to allocate budget in the best and most optimal way so for us it was all about you know can we really really understand what conversion path these people are going through across all those different types of touch points in order to be able to optimize our spend in the you know in the best way that we possibly possibly can and so having some of that data from GA has helped us to build one is now a truly data-driven model but isn’t just using simple rule-based heuristics that sort of apply to everyone and instead is creating completely customized attribution paths for each and every each and every one of our acquisitions that we can build up over time to give us a much a much more accurate sense of exactly where we should be spending our money it in terms of requiring customers that we just trim the clock before so that’s been that’s been really really cool I’m sorry I think I’ve majorly run over John but yeah thank you very much for your time everyone thank you I will on them thanks for that guys that was really good but yeah we yeah you went into so much detail but I think we’ll we’ll quickly fire on now and we’ll come back to questions actually well I think my save the questions for for Friday so if you have got any other questions you want to fire through ping them through and we will we’ll take a look at them we will make sure we answer them on Friday so I’m going to do I’m going to dip straight across now and we’re going to jump into our two minute case study so chris is going to take us through the next case study so just to if you’ve watched seen this before reminder i briefed my team two to come up with an two minute case that each day it got to come up with a slide that’s got some cheesy icons on it and then give us a quick two minute explanation as to what that is so here you go you can see that the two minute case study number three for Wednesday and have a quick look at this slide and see what you think this

might be but I will then hand over to Chris who’s going to fire through and talk us rapidly through what this case that is telling us they were – Chris thanks right so yeah I I got a bit you know too literal with the icons at the end there and I did just put google dates to do reports at the end because I felt like it you know adequately showed their the work they had gone in in this project so yeah apologies I’ve gone slightly off brief in that regard but so the work that Connor and John and this where it links in have spoken about I guess shows there’s the power of in-depth tracking and date for analysis but the example I have here shows that you know we can have a less complicated project in terms of tracking standpoint but it could be very complex for example from a logistical standpoint so hopefully this can show you how accurate data and measurement can be vital to ensuring success even when that data itself isn’t so complicated so the client I’m gonna speak about is Toyota Toyota have over a hundred eighty centers and dealers all across the country and each of these centers run local marketing campaigns this is all coordinated centrally but center owners want to know how many people are using their websites how people are using those sites and how many inquiries and test drives and things like this marketing who’s driving the previous reporting process for this as defined by this man standing next to the bulging stack of paperwork it was really time-consuming and cumbersome so that the process was that data was downloaded it was analyzed it was split out by each of these centers and then a new report was manually created for each Center each month and those were then sent over to the the center owners and the dealership owners and given the number of centers in the network this was practically a full-time job so when we came onto the project we saw that potentially we could make this more efficient than by using the Google marketing platform more effectively we could have a really positive effect and that outcome on the process so our solution was two-phased firstly we ensured that we had a central point of data collection and that the data we were collecting was as accurate as possible so in this instance we used a rollup GA property that contained data from every single Center in the network so it didn’t matter if you were on a Toyota website up in Newcastle or down in Bath for example you know you were always being recorded by this one GA prophecy traffic that we had in there events and goals were all audited to ensure that every user journey was being measured correctly regardless of which website that user was on and by using this one central property we ensured that every Center was reporting on exactly the same basis so that we could draw comparisons we could we could use benchmarking and those you know comparisons and benchmarking efforts would be valid once we knew that the data was accurate our next phase was to automate the reporting process which was the bit that you know took that the most time using data studio we made a template report for one center this was then sent over to Toyota for a detailed QA and then there was a lot of back-and-forth making sure that report was exactly you know what they wanted to see what the dealers would want to see once this reporters were approved we rolled it out over these 180 plus separate date dates to do reports to 180 centers which allowed each business owner to see useful statistics from their individual center the stats we gave them included traffic volumes things like lead generation by the different different kinds of marketing activity and some benchmarking stats both regionally and across the whole network and the outcome of the project was that a vast amount of time saving was made for the future people didn’t have to manually make these reports it also gave us a better understanding of what those user journeys were and it gave the center owners themselves more visibility over their own website performance giving them a reason to sign up for potentially more marketing activity in the future so hopefully you can see that you know just with a few tweaks in GA and then using data to do as well as the report we can really you know add a lot of outcome and you know performance impact to websites and web traffic so yeah thank you very much cheers Chris that was great so that’s just gives a different perspective so we wanted to make sure we had the detailed I talk today that went through the challenge and great solution we came up with a planet and then just to finish it off with a different perspective it slightly different one which is more about the brilliant dashboards and reporting that became it with Twitter but they’re just two examples of lots of stuff that we do within the conversion analytics team so we will quickly wrap up now just a reminder of what we’ve got on next so tomorrow at 4 o’clock we’ve got Jamie from pure electric who will be talking around how to get your CRO program up and running so that’s a great client side view of that so otherwise remember to get in touch with us to get your free analytics or landing page scorecard thank you very much to John and Connor for them for the main talk today appreciate your time Connor and also for Christa finishing off with that case study but otherwise hopefully see everybody again at 4 o’clock tomorrow thank you very much you

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