Streamline document signing with lead segmentation for Technology Industry

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[Music] hey I'm Jason at gagashi and today we're going to look at some lead targeting techniques or growth hacks basically you can use these same techniques for all kinds of different data but we'll start with a list of leads this data is synthetic so it's all made up so don't try to email these people and then we're going to clean up those email addresses by finding like disposable mail accounts and free consumer mail accounts and separating those from companies then we'll rank the companies by their Alexa traffic ranking which is something that Amazon used to offer but they sunsetted we're also going to compare it to a list of the Majestic million put out by a company called Majestic where they rank websites ing to traffic and other factors so we'll use that to segment our leads and we can compare the two ranking methods you could also do the same thing with other lists like Fortune 500 or maybe account based marketing list Etc you will use the crossfile B lookup function that I'll show you in the video so the first thing that that you'll want to do if you don't already have a giga sheet account is head to gigasheet.com and sign up for a free account the great thing about gigashi is it makes it easy to work with really large data sets in this example we're going to work with some pretty modestly sized data so we're going to start with this file called Majestic million CSV that I got from their GitHub site I believe you can also get it off their website I'll include a link to this file in gigasheet below so that you could access it if you want to use it for your own analysis so here I'm just checking out the file and showing you how you can explore the data that's in it we can look at the different columns that are available from Majestic and of course you can see the table next I'm going to jump into my Salesforce data that I've exported from my Salesforce instance here you can see typical stuff that comes out of Salesforce for each of these leads so what we want to do here is try to find the highest quality leads so what we're going to work with is the email address column so I'll drag that over to the left you can see here we have a bunch of stuff some of these are from known companies some of them are empty um some of them are from no-name companies first we'll head to the data enrichments capability here we're going to choose the email column and what I want to do is a format check here on the email addresses so this will check that the addresses are well formed and it'll also enrich our data with some other information so you can see what's happened here is it confirms whether the address was well formed by saying correct or not correct we also have a domain that's been extracted the Alexa rank the organization or whether the email is from an organization rather or if the email was free consumer based account or a disposable account that would appear here so let's start by grouping this data to just see what we've got we have 11 of these that are incorrect email addresses that are not well formed in this case they're just blanks so we want to get rid of all of those obviously and I'll show you how to do that here we'll right click on the group and click filter to this so that we're only looking at the incorrect we'll go to data cleanup and select delete matching rows delete actions can't be undone so it's important that you pay careful attention to this so that leaves us with only the correct well-formed email addresses which is perfect next we want to take a look at these domains and also the email disposition so this has marked them as organization which would be like an Enterprise or Corporation free which is like Gmail Hotmail Yahoo stuff like that and disposable so I'll use that right click function again but really what it's doing is updating the filter Fields you can build your own query to do this as well I just like to use that right click as a shortcut so here you can see lots of free Gmail Outlook Etc and disposable mail accounts there that are kind of like emails we want to delete all of these and just stick with the good stuff so I'll remove all those from our list and I'm left with organizations we have 347 rows of emails that look good now you'll notice in the Alexa rank column you'll see a bunch of these 999s that's the value that will enter if it's not in the Alexa million so we have a bunch of emails that are not within the top million I also noticed that there's some stuff that the email validation did not pick up where it has.com.com and I want to get rid of all those I just deleted one but let's delete them all so what I'll do is select the email column and I'll build a filter that says contains.com.com and I'll select that string and hit add so this will filter to all of those rows so you have 19 of them here I want to get rid of all of these as well now this is looking pretty good so I have 327 rows left what I'd like to do now is compare the Alexa rank with that Majestic million list and what I'll do is flip back over to The Majestic million and I want to bring some of that data into this file and what we're going to do is a cross file vlookup so I want to match on that email domain and I select the file that I want to do the lookup on which is the Majestic million there we go I'll select that next I want to choose the column to match on so I want to match the email domain with the domain in the Majestic million I could do a near match but domains are usually pretty and unambiguous so we don't need to do any fuzzy matching and I want to bring over values so I'm going to bring over the global rank value I could bring out other columns across so maybe if I had something like industry or market cap I don't have that data in here so I'm just going to choose the global rank because I want to compare the Alexa rank or use both the Alexa Rank and the Majestic million rank in my data so you can see that it brought that across where it matched like JPMorgan chase.com matches in the Majestic million as well so now what I'm going to do is build a filter and look at where the Majestic million calls it Global rank is greater than or actually let's do less than that means stuff that's ranked higher or the Alexa rank is highly ranking so this will take the top 5 000 websites from either the Majestic million or the Alexa traffic ranking so this is brought us to 120 of the 327 rows so there are 120 leads in these accounts that are at highly trafficked sites so now I could share this or export the data in this case you could share it with just specific people or you can make it public and give the link to anyone but that's it hope this was helpful