[Music] i'm john doran from gladfast consulting and today i'm going to show you how you can leverage performance analytics to display net promoter score widgets this will allow you to trend on your net promoter score you can dive into breakdowns or second level breakdown so that you can get a better picture for what's driving that score for your organization so if you're unfamiliar with what a net promoter score is it's a metric used in customer surveys which measures customer loyalty it's generally a pretty simple question in my example here i'm saying how likely is it that you would recommend test company to a friend or colleague it's generally a zero through 10 scale that could be zero through five but in this case i'm just doing zero through ten all of my nine or ten responses are considered promoters anything zero through six is considered a detractor and anything seven and eight is considered passive in the way a net promoter score is calculated is we take the number of nine and tens and we subtract the detractors from the promoters and then we divide that number by all of the surveys the number of all of the surveys that'll include my passive seven or eights so my example i have five surveys i have three promoters so three scores nine or ten one detractor so three minus one is two so two divided by five that'll give me forty percent so that's a pretty good score net promoter speaking if i look at this graph i just pulled up from google you could have a score anything between negative 100 and positive 100 so anything over zero is considered good once you get to 50 it's excellent and over 75 is considered world class so i'm going to show you how we can use performance analytics to get this score in service now and the idea would be once this is set up it will run daily so as different customer surveys are coming in your net promoter score is constantly changing so you'll be able to see and trend on that changing score i'm not going to go through creating every breakdown but you can also create breakdowns you know for specific categories or contact types right so you might have this survey firing on incidents where maybe one category has a really good net from overscore and another one is struggling so you'll be able to dive in and check that out right so that's one of the use cases for doing it this way using performance analytics you could also go down by assignment group or assigned to as well depending on how many different users there are so let's get started so i'm going to create my indicator source and the indicator source is basically i'm just defining my top level data set from where we're going to pull records in from once these indicators are created and tied to a scheduled data collection job the data collection job will run once for or query the database once for each indicator source so you might have seven indicators that use this but the data collection is only going to query that database once in the conditions there's generally a date related filter so if i wanted to have this run daily and calculate my changes daily i'll add that into the filter that you'll see below so i'm going to use the metric result table and these are my scores so if i add the condition metric category [Music] this one and created on today that will be my source i'm just going to make sure that i have the right filter here all right i think we're good so i've got my indicator source built out this will run daily uh you could schedule it monthly if you wanted to look at that type of frequency bi-weekly you know there are all these different options i'm going to stick to daily for this example and i'm going to create my indicator now all right so i'm going to pull in my indicator source my unit is going to be the pound symbol and the aggregate is going to be count value and nil i always set to zero most of the time this just you know if there were no surveys created on a certain day it'll just score that day at zero but it makes the graph look a lot better so you don't have missing data points direction i'm going to leave as none this just determines what you know what those performance analytics uh widgets look like so if an increase in score was positive we would say maximize however if an increase was bad like if this was number of new incidents we would select minimize and that way you know if my score goes up it might display in red for example or if it goes down it might display in green so that's sort of the direction fields but for the number of responses i'm just going to select none additional comments here i can add any additional conditions all of my conditions should be in the indicator source for this one so i can leave this as blank publish it on the analytics hub render continuous lines i always select this just makes the graphs look easier kind of connects each data point if there is something missing and that should be it so i'm going to save my indicator and i will move on to my bucket group so my bucket group is where i'm going to actually separate those numbers into those different categories i'll call it mps category my buckets are going to be detractors passives and promoters so we said detractors it's going to be 0 through 6. passive is going to be 7 and eight and promoters is gonna be nine intense i'll leave that empty so the way this works is if you have the same number as an end and start it's gonna categorize that record as the one that's starting right so this should actually be a seven so what we're saying is zero through sixes are gonna be my detractors if it's a seven it's gonna be start which is a passive and that's gonna include eights but if it's a nine it's gonna go to a promoter and anything above a nine loss with a promoter if i leave this empty all right so i'll save this now that i have my bucket group i can create a breakdown source and the fax table is always going to be pa buckets when we're working with bucket groups the field most of the time is always going to be sys id and my condition will be bucket group is nps category if i hit preview i should see my three my three buckets okay so that looks good now that i have my breakdown source created i'll create my breakdown i'm going to relate that to the source i just created and we'll create our mapping so the table is going to be metric results and we'll use the actual value field alright so now i'll just assign this to my indicator and that's that i'm going to create a scheduled job for the data collection i created these all of these scores today so i'm just going to do relative end zero days ago and we'll run it daily generally once this is up and running if you already had scores and you already had surveys being sent out you would do a historic data poll where you can go back 12 months six months however far back you want to start collecting scores you would run that once on demand and then you would set this up so that it runs daily typically in the early hours of the morning where the relative start is one day ago on the relative end is also one day ago and that way each morning this job runs collect score from scores from the previous day but in this case since i just created all of these surveys today i'm just going to set the relative end for zero so i can pull in data all right that'll execute i'm just gonna click into my indicator to see if everything looks good we should see our five scores and if i break it down by mps category we'll see the three promoters the one detractor and the one passive right so three promoters one detractor and one passive so that doesn't really show us much we don't have the score yet but we can use these breakdowns to get that score so i'm going to create a formula indicator next and these indicators don't need to be tied to any data collection jobs basically they use an indicator that already has scores and it relates them to a formula where it can just give you what you're looking for in real time so let's call this one mps score we're looking for a percentage this time precision you know you can show one decimal point two decimal points and it will round to that i'm just going to leave it at zero here we're going to maximize the direction the higher the score the better previously it was just a number of responses so i left that as passive and my formula it's very easy i'm just going to select mps results my breakdown is category and my element is promoter minus now here i'm going to do the same thing except i'm going to select the detractors and i'm going to divide it by all of my scores so it's pretty straightforward and then to get a nice percentage i'll just throw it times 100 at the end again i like to select render continuous lines so i'll save this so now once we show on analytic sub it's your score you see our nice 40 so if i had this job running daily instead of one data point you know you could see a line graph which you know will show every score for the given date i only have one breakdown on that metric uh or mps results indicator and that is for my mps category bucket but you could always add more breakdowns right so you can dot walk from the survey to the task so you can get you know incident fields you can break this down by category contact type all of those types of fields states typically this survey only gets sent out when the state is closed but you know i think you get the idea and you could always once you have multiple breakdowns there's this collect breakdown matrix button it really is kind of redundant when there's one breakdown but what this does is when there are two it allows you to go two layers deep so if i have a 40 score looking at the analytics hub here i would be able to look and say all right i have a 40 score what's my score for hardware incidents i can click into hardware incidents and then i could say what's my score for this uh so you can go down a couple layers that's the idea so i hope this was useful again i'm john doran with bifast consulting and feel free to reach out to us if you have any questions or comments thank you [Music] you