You are probably wondering what the hell is hyper-personalization and why do I need it? Facebook, Twitter and Google provide me with plenty of targeting options already. Right?

Well... if I misrepresented you then I am sorry though what I am about to describe provides you with an arsenal of data that you can then take to Google or Facebook and run cheaper advertising campaigns, that target exactly the people
you want to hear your message.

But I digress... first I am going to explain how this three pronged method works and then I'll illustrate how it can be done (or at the very at least provide the tools to help you).

Step 1: Gathering Advanced B2B Data

There are plenty of companies offering you the next best data set or overcharging you for a set of unverified leads they scraped from LinkedIn.

For that reason I won't discuss extracting lead data from LinkedIn because you can find dozens of bots, and tools out there that will do the job, kind of. Don't get me wrong, I love LinkedIn, it has provided me with many a clients and website traffic.  

Want to get connected? I'm accepting invitations here.

Anyway moving on...

By all means harvest data off LI but you'll be missing some truly personalized information. That's why in this section, in addition to anything LI and similar business directories provide I take that information and use it to find myself even more information like:

  • What the lead's interests are? (Snowboarding, axel grinding - whatever that is. Put it into the spreadsheet!)
  • The groups they belong to across their social profiles (Facebook, Twitter, LinkedIn).

    This starts to paint a clearer picture of the kind of person I want to sell to. Moving on...
  • Their past posts on these social platforms, filtered by keyword.
  • Locating their colleagues (particularly their boss) and unearthing any media they may have shared online.

    Note: I want to make it crystal clear that although this is starting to lean towards somewhat of a malicious side, there is nothing but purity in this prose. As you'll learn later this media isn't used for what you might think. Come on, after all, we're marketers, not telemarketers!
  • Approximate income status etc.
  • Any news appearances, or latest press releases they were involved in.

and much much more.

As you can see in the right hands this data could be gold in your communications with a prospect. And what's even better because this is data you harvest, it slots nicely into your spreadsheet, later to be used in a mail merge when you send out
your mass, hyper personalized email campaign.

And guess what? The majority of this can be completed within a Google Sheet which I'll show you a little bit later.

Before we end this section here are some tools that might come in handy.

  • Web Scraper extension for Chrome
  • Data-Miner (possibly... personal preference)
  • Linkedin Helper extension for Chrome
  • => extraction robot builder
  • And more importantly, Google Sheets and the following codes:

=IFERROR(CONCATENATE(IMPORTXML(A2,"//*[@id='b_results']/li[1]/div/div/cite")),"URL Not Found")

Don't concern yourself too much with the above line. In layman's terms it pulls returns the first result from a bing search, and if it can't connect or find the result the spreadsheet cell reads, URL Not Found. Otherwise, it will be a social handle like so:

WHERE A2 ="[keyword1]+[keyword2]"

As long as you have the search terms written correctly, you can use the same method to find other information (not just from search engines, but business directories or directly from social platforms. I'll post my actual spreadsheet examples soon.


Used for appending + mass generating LI URLs that link directly to a user's group/interests. This makes the extraction process much easier. In fact, using the CONCAT and CONCATENATE functions will allow you to connect strings and data in different cells together. Super helpful.

Anyway, I may have given away a little too much already. So, let's move on.

person using black and gray laptop computer
The data hunt begins! Photo by rawpixel

Step 2: Setting Up Personalized Automated Email Campaigns

A while back I wrote a post detailing my favourite add-ons for Gmail. In this example, I am going to refer back to a couple of those extensions, and several new ones.

Let me ask you a question. Which email service provider (ESP) are you using for your email marketing campaign(s), funnels, or automated opt-in response?

Surprisingly, it doesn't matter  all that much at the moment. As long as they allow you to upload custom data, and behavior based automatic follow-ups they will do just fine. Personally, I prefer connecting SendGrid to something like GMass and getting that deep data. However, there are many great companies like Reply,
Elastic Email.

The next thing we do is pretty simple. We upload our new list of prospects along with all of that extra data and start copywriting a series of emails which would touch upon some of the information you have gathered.

Latest news article? Include it! Link to their Twitter post? Reference it in your email. Prove that you have done your research about your prospect and you will receive a much higher open, click and conversion rate.

Note: On average it still takes 2-3 emails to get a conversion so don't be bummed out if you don't strike gold with the first email. People are busy, they don't always check their phones etc. Hell, I barely reply to emails anymore.

Step 3: Personalizing Your User's Landing Page Experience Via URL Parameters

two people holding hands
Personalized Landing Pages Are THE Ultimate Way To Build Rapport | Photo by rawpixel / Unsplash 

This might sound crazy but what if I told you that the link you include in your email or Adwords/Facebook ad could automatically be unique for each person (without the recipient knowing of course) and when they click it, the landing page they are treated to is completely customized and personalized to them and their brand? Pretty cool right?

Well... it's actually easier to do than you think. Remember all that data we captured in step 1? The trick is to append that data into the URL, as per below. These are known as URL parameters or query string parameters.!

The landing page accepting this link would read it, and would automatically put the different data variables you inserted into the spots on the page you allocated. See why it's good to have plenty of data on your potential lead?

Another trick you can use that is in the same vein as the above is to have your opt-in forms automatically prepopulated with your user data. To help speed up their journey to 'yes'. Similarly, you would append your user data into the URL except the variable names would be the ID names of your opt-in form etc. Still pretty handy though.

Note: You can still include your Google Analytics code within this URL structure without breaking anything.

Retrieving this data is best done using Javascript or another server side programming language, but again there many companies you can use to simplify your process. For example, here is a WordPress Plugin called URL Params which will process this for you.

Other recommendations

  • Ultradox (great plugin for Gsuite Apps)
  • Unbounce
  • Zapier (particularly their web hook function)
  • Instapage

And that's it. I hope you enjoyed this post, it is still in development and will be updated regularly as I run more tests and discover, faster, better and more efficient ways to get data into the hands of people who know how to use it.

P.S If you're tech savvy, you could use Google Sheets + Ultradox + GMass to make this process run on repeat without needing intervention from you. This includes lead generation, url manipulation, and emails being sent to each new recipient on your sheet.

Hm... definitely food for thought. Thanks for reading!

Part 2: How To Create The Perfect Custom Audiences on Facebook & Google

(Using Your New Data)

Enter your details below to gain access to part two. Don't worry we don't bite :)