Hey guys, this is a Marketo office hour session dedicated on the Marketo scoring. We'll see what is the purpose of the scoring in Marketo. What to be scored, what are the good practices of the demographic scoring, the firmogrpahic scoring and the behavioral scoring, and what are the traps and what you should not score. And to end that, we will see some other business cases where the scoring might be useful. Let's go. So what is the purpose of the scoring? Basically, it's to help your sales to prioritize their hot leads. If you have Salesforce or Dynamics, you may have this Marketo Sales Insight app in your CRM and you recognize this list we have and Marketo gives you stars and flames to indicate to you the most urgent and the most hot leads to be worked on. As you know, in Marketo, there are too much information now. If you look at an activity log of a lead, you will see that everything is recorded and it's not humanly possible to deep dive into all the activity logs of all your leads and to find who is the right lead to push to the sales. We need an automatic process to filter out who are the most important lead and who are the lead doing nothing. That's where the scoring comes into play. Basically, you will put some points on demographic attributes of the person, on firmographic attributes of the company, on behavioral data, and this will sum up into a score that Marketo and your CRM will transform into stars and flames thanks to a relative scoring and a relative urgency. So basically, the scoring is here to have your sales gain a lot of time. You want to automatically detect who is ready to talk and save time and energy for the sales, too much data to analyze, yeah. And yeah, it's a process that was used at first for new business. So basically, the process is you are doing a lot of marketing. You have too many leads to send to your sales unit to filter out who are the best leads and the one who have the most interest in your brand and are the most likely to convert. And that's where the scoring comes into play. Marketo has this statistic saying that a lead that is well scored pushed to the sales has eight more chance to be converted than a random lead to push to the sales. So that's how important is your scoring. A quick note here on the philosophy of Marketo, how Marketo is built from the big data to the revenue modeler. So big data is a big word here. It's not really big data. It's all the information you have in your lead profile, all the fields, everything that's come from the CRM and all the behavioral data. Too much information to manually look at that and analyze that. So the lead scoring is based on all this information to sum up basically everything into one or several scores. And on top of that, we put usually the lead lifecycle program that will push your lead through different statuses from cold, lukewarm, warm, MQL, SQL, opportunity, opportunity won, and eventually a dedicated customer lifecycle if you are more mature. But that's usually the steps you have plus steps to recycle the lead that has been discarded by the BDR or the inside sales or that you have lost at the end. On top of that, usually the lead lifecycle helps to create very personalized nurturing because you may want to talk to your leads differently if they are at the beginning of the cycle, if they are cold, or if they are about to close a deal because they don't have the same knowledge on your brand. And on top of the lead lifecycle and the nurturing, usually have the revenue cycle model. You know, this is this app in Marketo that helps you calculate conversion rates and time spent in each step of the lead lifecycle. So what is to be scored? Oh, sorry. It's in French. I will translate that, but it's not very difficult to understand. Once you have played with your score a lot, one truth that becomes clear is that you have to collect the most of the information into Marketo. If it's not into Marketo, you cannot score basically the behavior or the information of your lead. So for instance, everybody starts with the emails. That's the level zero of the score because you may want to put some points on the fact that someone opens or clicks in an email. Careful here because the information starts to be less and less reliable because the email clients tend to not to give old information or give wrong information. But for instance, let's imagine you have agencies throughout the country. A very interesting behavior to score would be to detect the fact that a lead enters an agency. So how it's not, I'm not saying it's easy, but that would be crucial to be included in the scoring. So there would be several ways to do that. But for instance, we have a lot of videos just like this one. So it was very important for me to be able to score the fact that someone looks at a video more than 25% of the length or 55%, 75% of all the video. So that's why I chose a dedicated video hosting solution that is sync with Marketo. If you download content on my website, whether it's an ebook or an infographic or anything behind the form, this will be scored. If you play with a quiz or an assessment on my website, this comes into my Marketo and this will be scored. So I tried each time I put new touches in my buyer journey to integrate them with Marketo, try to collect as much data as possible and score that. That's very important. So we have usually split all the scores into a behavioral score, comportemental in French and the demographic, filmographic score. That's all the attributes you can get on the person and the company. And there are two other splits, one of the splits with two categories, sorry, implicit and explicit. So implicit behavior will be to detect everything that the person does on your website. That would be done through the Munchkin. The Munchkin will tell you each page the person is viewing and even if he clicks into the pages, you know that you can enrich that with some events. You can push to Marketo if the person does something special on your websites, for instance, entering, logging into your portal, clicking, downloading an invoice for instance, or things like that. You can do that. It's not standard in Marketo, but you can use the Marketo APIs to push this information into Marketo. The explicit behavioral would be all the information you collect at some point in the buyer journey. For instance, if you have put a tick box in a form saying, I have a project or I want to talk to a sales, that would be great to score because this indicates a behavioral that's really interesting for you. The bound, usually it's budget, authority, need and timing or timeline is also a great indicator of the nice behavioral, a behavioral you want to score very positively. The demographic, filmographic parts in the implicit would be everything you collect through the IP address of the person, whether it's the geographic or the company, and through the company, it can be also the industry and the size of the company. That can be interesting for you. An explicit demographic would be all the information you will collect through the forms, meaning job title, is the person decision maker or not, when which service is working on, everything you collect through the forms. The big question here is, how do we allocate points correctly to all those behavioral data and demographic, filmographic data? That's a huge, huge question. Usually everybody starts with, you know, those two Marketo programs that you can download from the library that gives you some example of points you want to attribute. The first method would be to draft a standard biojourney and to look at some of the biojourney of your customer prospect, to understand what they did until this opportunity was lost or worn, and to understand the number of touch and try to allocate points on all those behavior and attributes you collected throughout the biojourney. This is a manual process that we all did all along for years. Now with data warehouse, with data scientist, and now with artificial intelligence, we can go beyond that, because you can, for instance, extract all the opportunities you have worn and lost for two years, for instance. Extract a number of fields on the opportunity, on the contact attached and the company of this contact. So you can extract, for instance, a huge Excel spreadsheet with, let's say, 200 cons and maybe hundreds of lines, depending on the number of opportunity you had for two years. Try to put some behavioral data on the contact. That would be not so easy to do, but with a data warehouse, that's something you could do. For instance, I've filled on the person saying, here's the number of forms this person has filled out the last six months, one year, two years. Here's the number of clicks in emails we have for six months, one year, two years. So this is how you could bring behavioral data on the person and send that to your data scientist or to Chat GPT if you want to try to find patterns. What are the key attributes or behavior that would explain the fact that this opportunity are won or lost? And that's something we'll see next week. Sypher.ai does automatically all the time, every hour, every day. So this is something you can do one shot every six months or every year. And that's a huge work, but now we have solution and I will have this market office hour dedicated to Sypher next week. We have tools to do that automatically. That would go beyond a bit of instinct, let's say instinct. Now we can really base our scoring on data and have the scoring evolve through time to constantly adapt to the change of behavior of the prospect. So if you want to scientifically attribute the points to the best attributes and behavioral data, you may end up like me to create some fields on the person or the company that will bring on the person a lot of behavioral data that's in the activity log or in the campaigns. That's a lot easier to then analyze the data. So you could also push everything into the dataware and try to analyze everything in this gigantic data model, but it's not so easy. So here, for instance, I have aggregates that tells me, here's the number of forms this person has filled out in six months, one year, two years. Same for the attending market office hour for one year, two years, six months, or the number of web pages the person has seen on the website for six months, one year, two years. I could go down like that with a lot of behavioral data and that's the limits of the model because you cannot create 1,000 fields for having behavioral data on your person. And on top of that, you are obliged to do choices here. So what if reading infographics is crucial in the biojournalist sorry? And it's not, I've not calculated aggregate for that on the person. I will completely miss this point. So the better solution would be to send all the campaigns, the programs, and the behavioral data into the dataware and analyze all this huge amount of data. Just to finish on what to score, what's great with Marketo, you know that, is that the scoring is completely at your hand. You're free to create whatever you want in the scoring to score whatever you want and to allocate the points. That's one great advantage of Marketo compared to other competitors. And you can also create as many scoring as you want. So obviously the person score, but we'll see we have behavioral and demographic, firmogrpahic score, but you could also create a dedicated score, for instance, for HR. If your company is hiring a lot, you may want not to score, not to score only the prospect and the customer, but the people coming on the website to find a job. So that would be a dedicated scoring, very helpful for the HR before the interviews. So that's another business case that could be useful for the scoring. I will talk more about that at the end. What are the good practice of the behavioral scoring? So in Marketo, that's the easiest to score as long as you have brought the behavioral data into Marketo, into the activity log, whether it's native or it's brought back into Marketo with custom activities and APIs. You can do that, for instance, login to your portal. Here we will score an event triggered by the prospect. So that's the definition of the usage of the trigger in Marketo. So it's pretty easy just to find the right trigger and add the point. So here, a quick note, be aware of scoring too heavily, the emails opening or email click, because the disinformation is less and less reliable. For a long time, opening was not so reliable, but the click, thanks to the clickboards, even if Marketo has developed a way to intercept some of the clickboards, the click are also less and less reliable. For instance, I think Apple doesn't transmit anymore to Marketo to click in their email. And a frequent trap I see often on the behavioral scoring is to score too much the webinar. You score the registration, you score the attendance and you score the replay, meaning that the webinar, let's say you put 10 points each time and the webinar may end up with 30 points compared to, for instance, five points you allocate to reading an infographic. So that would overscore your webinar. Let's have a look in Marketo, how this scoring program works on the behavioral data. So you know, a good practice in Marketo is to have only one scoring program throughout Marketo. You don't want to scatter all the scores campaign in all the campaign. All my scoring campaign are within this program. If I want to maintain that, it's easier. And I'm using heavily the scoring token here. That gives me a clear view of all the scores. So here, everything starting with a B ####the prospect. So here you see I've differentiates the points. I give for the customer and for a prospect,usually I give less points to the customer than to the prospect. Everything starting with D is demographic. And so pretty easy to maintain. So good practice here, use heavily the tokens and only one program score. You know that in Marketo, the token here and in every program or folder is the, I think it's the only object where if you put the token in a smart campaign below using the name of the token, and then you change the name of the token here, it will not change the token within the smart campaign. That means that the link between your token here and what you put in the smart campaign will be broken. Contrary to, for instance, landing page name, email name or program name, if you change the program name, everything will change where you use this program. So the token is a bit tricky to use because once you've created your token, it's not a good practice to change the name of the token unless you go through all your smart campaign here and review all the tokens that have been changed. That's usually a huge work. So all the smart campaign will work on the same pattern here. Usually you have a trigger that will be chosen depending on what you want to score. So here I want to score the click link in any email. So I will choose the click link in email trigger or the click link in sales email, the one I will send from my CRM. I will put some constraints saying, I don't want to give points to anyone clicking on unsubscribe link, preference center, or you know the web view link you have at the top of the page saying view as a web page. Here, it's just a filter saying allowing me to differentiate the scoring for a prospect or for a customer. So active meaning customer in my CRM. And usually you have this list of people you want to exclude from your scoring. So usually I exclude obviously all the employees who will have a much heavier behavior than the prospect and the customer on my website. We will open all the emails, fill out plenty of form. So if you score your employees, they will have crazy scores and will you know overwhelm the scoring system due to the score, massive score. And you want to also remove from your scoring anyone who has behavior, not standard, let's say. You want the score to be in a certain range for all the prospect and customer you want to score. Why is that? Because you've seen in Marketo and the CRM will turn the scores, the absolute scores into relative scores. So the scores have to be in a certain cloud that's consistent. If someone is far beyond or far below, he will have three stars and nobody will have three stars. So you want to eliminate anybody who has a strange behavior. So let's quickly have a look at this exclusion list. That should be in my database part here. I will exclude… So the disqualified lead, meaning people not matching with my target audience. And usually that's done automatically with a certain criteria that disqualify people. Here, we have a number of statuses, person statuses that disqualify automatically from the scoring. So fan and ininteresting meaning fan and the reverse is ininteresting. They are manual statuses I put on people that I find to do too many things. And I know those people will never be customers of mine. So I want to exclude them from the scoring. That's where I have those special statuses that I manually put in my CRM. And here I exclude also the employees of the Merlin Leonard and the people who are partners of Merlin Leonard. I manage in my CRM a lot of partners and I don't want those people to be included in the score, obviously. So that's the basic structure of my smart list of all the smart campaigns for the behavior. The flow will be always two changes score, one for the status score, which is the person score in Marketo. And we will use the adequate, the relevant token here, which has been defined, you remember, at the tokens tab in the program level. And I have this behavior score here. So why is that? When you download the two standards, scoring program Marketo gives you, remember, if I click on a folder here, I have import program, I can access the Marketo library here. And in this library, I have a number of programs. At the bottom of that, I've got two programs scoring, behavior scoring, demographic. And those programs asks you to create two fields, two scoring fields in Marketo beforehand, behavioral scoring and demographic scoring. Once you've done that, you can import those programs that are very good to start your scoring. So that's what I did, but I don't merge everything into one program with one folder, one subfolder behavioral scoring. And that maybe should be behavioral scoring, I think. Yeah, that's better. And one demographic scoring. So in Marketo, you cannot say like in Excel, for instance, at any time, I want my person score to be the sum of the behavioral score and the demographic score. So as you cannot do that, you are obliged to have the person score moves in the same way as the sub scores. So each time I change my behavioral score, I have to change my person score the same way. And we will see it will be the same for the demographic score. As soon as I change the demographic score, I will have to change my person score adequately, resulting in the fact that the person score is the sum at any time of the two sub scores. So it will be always in the flow of the smart campaign for the score, those two actions. And the schedule, the last parameter here is, this is where you can play a lot with this parameter that we don't use so much in other campaigns. It's the number of times a person is allowed to go through this campaign. So for instance, for the click here, I don't want the person to go every time because of the click bots. If I send an email with, I tend to send emails with a lot of links at the bottom of the email for the, for instance, the Marketo of our history. That are links that point to my blog. I don't want people, I don't want the click bots to click on my 30 links and get 30 times in this campaign. So that's why the bot will click, will go through this campaign for the first click and then during the next hour, it will go, it will not go through this campaign. So usually for the emails and the open emails, it's once every hour I put. So here, download any PDF from emails, the same campaign, but, you know, I've got a filter here on any PDF data, and I excluded PDF from this campaign because it's another point. So it's like two points here, it's like five points. I've got the forward to frame because I include that in my email. So anybody who forwards to a friend an email, thanks to the Marketo solution, the Marketo widget, we'll get points, opens an email. That is something I put here, but it's something I will certainly very soon remove. So the trigger are opens email and also sends email, sends email. Again, that's the email I sent from my CRM through Marketo, but from the CRM. So very, not a lot of originality here for the webs. What do we have? This one is not activated because we don't do ads, download content from the web. So here it's lots of campaign based on the forms and basically that's all the different forms. So here, sorry, here this one is click on a link containing PDF on my website. Here it's fills out any form that would be a form not containing a special keywords like design, which is for the preference center and sub, newsletter, office hour, or contact well. Fills out contact form that will be for the forms containing the keyword contact, but here I have to, I've just one contact form for friends and one for English. So I just named my form here, it's better. Registration for office hour. That's a dedicated form also. Yeah, I've got the two old and the two new office hour. I have this video system that's integrated with Marketo, it's 23. So I can manage dedicated 23 forms on my video, for instance, for the market office hour replays, you've seen that you have to sign up to the video if I don't know you and if you are not known into Marketo, I collect that into Marketo and that comes into Marketo as signs up on video. So that's a great integration that creates custom activities in Marketo, one of them being the sign up on video. Subscribe to newsletter, that's a dedicated form again. It's a special form here and subscribe from newsletter. This will bring negative points. If anybody unsubscribe from the newsletter, which will switch this parameter from yes to no. Visits 10 pages in two days. So that's something we can do in Marketo, but not on the training courses because that's too many pages view. So that excludes all the trainees that are currently taking an online course in my training system. Key webpages again, that's for the pages containing special offers, training, contacts on Marketo. Multiple webpages in one day, that's again. So yeah, we have multiple one page in one day. So three page in one day and 10 page in two days. That gives a number of points. Xeno is my chatbot, so it's not the Marketo chatbot. I used this chatbot a long time before Marketo came with the chatbot. I'm still using it. So again, there's a native integration between Xeno and Marketo that helps me understand if someone has booked a meeting with me or someone has interacted with the chatbots or the chatbox. So that's pretty great. What do we have in other interaction is the satisfaction survey or the quiz here. So again, that's tools that are integrated within Marketo. So here the quiz app will push fields on the person, especially a quiz date. As soon as the quiz date will change, it means a new quiz has been filled out. Those quiz will be stored into a custom object in my Salesforce. So as soon as those fields on the person changes, Salesforce copy all those fields into a record in my quiz custom object. And this will come back to Marketo in a custom object. Rempli un quiz, it's filled out a quiz. So here it's the person. And the quiz name must not contain satisfaction. Otherwise here it's contained satisfaction. So that gives points that are different based on the fact that it's a satisfaction quiz or an assessment quiz. Success, we have Events. So here, those are based mainly on the program status in the channel. So channels are great for that. If you go through a certain step in your channel, so here the event, if you are attended, I'll participate in French, basically you get the point for attending. And here with the meeting, it's another step in my event channel, which is a participer avec rendez-vous. So it's another channel. So this is the, yeah, obviously the event in Marketo, the events will change the status of the leads in their program accordingly. And this form, sorry, this scoring program listens to all the events that are active in my Marketo. Office hours, that's another meeting, another channel that is listened to. And here it's, yeah, MLH office hour events attended, again, trade show, visit booths, same. So here video, we have, if you watch any video more than 50%, I think it will add more score here based on 25, 50, 75, and 99. So here, for the moment, I just put one score for above 50. We'll, I think, go a little bit beyond that. Webinar success is the fact that, again, the program status of the webinar channel changed to attended. Here it's attended on demand, I think. You get the point only if your previous status was not attended. So if your old status was attended, you already have points. So we don't want to add points on the fact that you attended. That's my choice. So you get the points only if you attend on demand, but you didn't attend in the live session before. We have some negative points here. So unsubscribe, again, gets you minus 10 points. Yeah, so as soon as the attribute unsubscribe, for instance, switch to true, you've got the token for the unsubscribe, but I have the reverse point. If someone resubscribes, it happens sometimes. So if your unsubscribe was true and became false, and this has to be done by the customer or the prospects, not me, you can do that, you get the plus 10 points. Here, as soon as you switch to those statuses that are indicating that you are excluded from scoring, so when you are recycling this qualified fan and ininteresting and you were not in those statuses, you switch to zero for person score and behavior score. You lose points if you do not do anything for 29 days, basically, and your score is above zero so that you don't get towards minus infinity, but here you will lose those points. I think it's 10 points or something like that, but you can go through this campaign only every 30 days. And here, if you are in the exclusion list of the scoring and your score is not zero, every evening, everything is put to zero. So that's for anyone who went through the net, you are stuck to zero with this campaign. So now, the demographic scoring is a bit more complex. Why is that? In the behavioral scoring, it's pretty easy because we will add points as soon as the person triggers something in Marketo, and it's one shot. So for instance, if you attend an event, you just have to detect when the person attends the event, you give the point and it's done. The person can never not attend the event. It's not possible. Here, with the demographic scoring, if #### If the person enters a certain state, for instance, if the person is a decision maker in his current job, you give points. But the person will evolve over time, so this person may change jobs and end up in a job where she is not or he is not a decision maker anymore. And at this point, you want to remove the points for this person. So for the demographic and firmogrpahic scoring, you have to think about when to add points, but also when to remove points, because here we will have people entering and exiting states all the time. And that's one of the drawbacks of the demographic scoring Marketo gives by default. If I understood correctly, they only give points for the first time. You may think, okay, Sylvain, that's great, but why don't we recalculate every evening all the demographic and firmogrpahic scoring? And we put everyone to zero and then we recalculate everything every night. That could be a good idea. Unfortunately, if you use Salesforce Dynamics and you use this Marketo self-insight with the relative priority and relative urgency, the urgency triggers as soon as the score changes. So here, if every night you recalculate a massive amount of demographic scores, Marketo and the CRM will believe that everyone has changed during the day and you will have everybody having an urgency of three (frames) all the time. So your urgency will basically become unusable. So it's a first good idea, but not so great if you're using those flames and those stars. So the flames essentially, the stars should not change. So what I love to do, we'll see that, is to detect as soon as a person enters the state, but to make the effort to detect when the person exits the state so that they can remove points. But this obliges me to create double tokens, one with the positive score, one with the negative scores. We'll see that right away. So here, try these, use negative scoring for invalid or generic email address, first name, last name, and use positive scoring when you detect the customer of your competitor. Let's have a look at what I did in my Marketo. Demographic point here. Let's take one very simple example. For instance, the service. So services, basically you're working in marketing, sales, direction, or management, customer service, whatever, communication. And I've decided that there are a number of services that are very interesting, some of which are interesting, and all the others. So basically I've got two points. Let's see on the tokens here how does that work on the demographic scoring for services? Yeah, so services, very interesting, it's 10 points, medium interesting, it's plus five points. But you see here, I've created this token, service interesting high reverse, and service interesting medium reverse, with minus 10, minus five. And I will have to manage that. So the first campaign is when a person enters the state. Here, it will be with the data view changes. So I've got this field service in my CRM that is a list of value. So I have a lot of work before that to deduct from the job title, which is a text field, the correct service. And I've got campaigns and Marketo working all the time based on keywords to say if you are a CMO, the service is marketing, for instance. So if your service, the new value of your service is one of the six services, I want to give point two. So it's management, marketing, sales, customer relationship, information systems, and communication. And your previous value was not in those six, so it means I enter one of those six. Or the person has just been created and the service is one of the six. So why do I do that? It's to cope with the creation event and the modification event along the life of the person. If the person has just been created either through a form or through my CRM, these triggers will activate and this filter will be very important. If the person exists in my CRM and Marketo for a long time and suddenly the service changes because the person has just changed his job title in the form or I decided to change the service in the CRM, this will be this trigger that will activate, not this one. And the filter basically here is the same as the constraint I put here. So the filter is useless here but it will be useful for this trigger. So here be aware, if a person is created, the data value changes don't trigger. You can look at that in your activity log. If a person is created, you don't have a lot of data value changes to indicate that this field is a switch from the value null to something. You have to use the person is created trigger and a filter to correctly trigger this campaign. The flow will be exactly like the smart campaign for behaviour except it will be the demographic score here not the behavioural score. And here I've got a choice saying if the service is direction general which is management, which is the one with high points, I give the token high, otherwise it's token medium and the same for demographic score, it's the token high, token medium. So here this campaign manages the fact that you enter either the high service, the management one or the five others, medium one. Now, how do I manage the fact that I exit for instance from the high position, the direction general management. I say again with the data value changes, if your service is not direction general management and it was previously direction general and I'm not excluded, I give the reverse point. So service interest in high reverse, service interest in high reverse. Same for medium. If you were in one of the five services here that give medium point and you're not anymore in the new value in those five, I give you the medium point. So usually you have one campaign to enter and you can manage the different points through choices but to do the reverse, you have to do as many campaigns as you have of case. Here I only have two cases, high point, medium point but if I decided to have four levels of points, high, pretty high, medium, low, I would do one campaign to enter the state and there will be four campaigns to exit the states. Basically that's everything is the same logic. So one key point here is to work on fields that are based on the list of value and obviously the data quality here will be crucial. You have to make sure that all your leads have the right values. As soon as you have bad data in your list of values, scoring will not work anymore. So here, some advanced campaign. Customer of competitor, I'm not really using that because that would imply that I have put, for instance, on my opportunity of fields saying that I've detected that this account is a customer of one of my competitors and who is that? I've not yet done that. Generic email domain, that would be if you are into this generic email domain smart list. And why is that? Yeah, here I've got a number of generic email domain. Marketo has recently given a list of, I think, 4,000 or more or less generic email domain in the admin option global validation rule. So I can use this list here. I should update this list with the Marketo list. Then if the person that has been created or whose email has just changed is in this smart list, then you get negative points and basically it's the same with invalid first name and invalid last name. You have to put people in a certain smart list that detect keywords here. It's not a lot of other ways to do. So here, that is a smart list given my market Markito and you have to update it. So that's it for the demographic scoring. So next, what is not to be scored? So I talked about a bit of that in the previous discussion. Usually you want to exclude basically from the scoring system, any person who is not having a normal behaviour, normal being whose score will be within the acceptable range. So let's say, let's imagine you decide to have a range from zero to 100. Any person who will have such behaviour or such attributes that the points will go way above 100 because they, for instance, open every email, fill out a lot of form, look at a lot of videos. And that certainly will be the employees because they are doing a lot of tests. Or the fans, meaning people outside of your organisation that have a huge interest in your content. They may be partners, they may be people who follow you but will not become, or have become already customers and you are following these people well. You don't want to be included in the scoring because you know them by heart. And I usually, for the touches, I don't want to score anything behind the fact that behind the sales. Why is that? My scoring basically helps me define who I should push to the sales. Once I've done my job, I don't want to collect any more information and score that because the sales will not base their process on the score anymore. They will, you know, the BDR or the inside sales will qualify the person and try to collect the budget, authority, need a timeline, and try to find out if the person is really a hard lead or not. And the sales will base the fact that he takes his phone and set up a meeting based on what the inside sales or the BDR has done. And usually they will not use the score. Or we could create a dedicated score for the BDR inside sales phase, you know, that will help the sales prioritise the hot leads. So there will be a global score that will switch the person from marketing to sales and then a sub score that will trigger only when the inside sales have received the person and that will score, for instance, the balance information, how well went the first qualification touch, whether it's a LinkedIn message, a phone call, and for instance, information that the inside sales or the BDR could collect on the account, the potential of the account, the revenue, the benefit that could bring to the company. So we could imagine a dedicated scoring at this point. And usually my scoring will reset to zero as soon as the opportunities lost or won or as soon as the inside sales or the BDR has rejected the lead and pushed back the lead to the marketing, everyone will go through zero. That's what my lead lifecycle does. So here, if you are disqualified zero, if you are refused by the event zero, recycle zero. If you are lost, a bit of weight, but you go to recycling and zero. And at first, I didn't have this dedicated customer lead lifecycle, so one was also recycling after that. But now you go through this dedicated customer lead lifecycle, but I re-initialised your behaviour score to zero here. Last topic, what are the other business cases of the scoring? So we talked about this, the possibility to use the scoring for HR, for instance. You could also create a dedicated scoring for your partner management. So I've got my partners in my CRM. I could create a dedicated scoring to rank how great are my partners and to have some partner marketing and everything. One other business case that is great is for instance, if you collect the areas of interest to your prospect either implicitly through their customer journey, what are the pages they look, what are the programs they're going through with success? What are the links they are clicking on emails or explicitly through preference centre, just like me. If I go to my preference centre. Here on my preference centre, I have this area where you can tell me exactly what you're interested in, in Merlin and Leonard. And I will try to obviously push you through the educational nurturing based on your preferences. So if you try to collect that one key issue here is, okay, you've told me that you're interested in event marketing, inbound marketing, customer experience, data quality, but which one is the first? And that's where a scoring dedicated to areas of interest could come into play. You could create as many scores as the areas of interest and I've got a lot, okay, I know that. And create small scoring program per areas of interest. So there would be one for event marketing, one for inbound marketing, one for customer experience, one for data quality. And each of the campaign will be filtered. For instance, if it's open email, click email, fill out form, you have to filter all those triggers on here, the email for event marketing, the forms of event marketing or for inbound marketing. So it's a bit of a huge work and this works well if you have set up a naming convention in Marketo for the programs with your areas of interest. Otherwise, it's a bit of a nightmare because you have to explicitly name each and every email or program for event marketing. So it's not easy to do, but if you do that, and for instance, you have those 20 scores on the person that you push to your CRM. In your CRM, you can easily have a field saying areas of interest one, two and three based on all the scores you have on those 20 scores. And that will help Markito prioritise the nurturing you want to send to the person. So that's something that helps you go beyond just tick box or checkbox for your areas of interest. That's a good way to start tick box, but the problem is that if the person or your system has detected five areas of interest for the person, which one should you start with? That's only with a score that you would have the sensor. That was a long session. I think I've covered a great deal of the scoring. If you have questions, guys, don't hesitate to ask me. I would be really glad to help set up the right scoring system for you and use for instance AI to fine tune exactly the points and which interaction you could score or you could come next week and see Sypher.ai that we'll use artificial intelligence for scoring. That's another way to do that. Talk to you next time for the next Marketo Office Hour. Have a great day. Bye-bye.