Rittman Analytics are a Certified Implementation Partner for Segment and we’ve implemented two of their services, Segment Connections and Segment Personas, on our two Squarespace-hosted websites; our main company site at https://rittmananalytics.com and the site we host the Drill to Detail Podcast website at, the subdomain https://drilltodetail.com. 

We use a single Segment Javascript tracker script installed on both sites that replaces all of the individual trackers used by Google Tag Manager, Hubspot, Google Analytics and other site analytics services we use, with the Segment tracker then routing all of our visitor interactions to these downstream platforms along with supporting customer data from Hubspot and mailing list sends, opens and email link clicks from Mailchimp.

We’ve configured Segment to use the same same Segment property ID across both sites so that visitors keep the same unique visitor ID across both https://rittmananalytics.com and https://drilltodetail.rittmananalytics.com so that when page view and tracking data from the two sites makes its way into Google BigQuery for analysis later on, we can measure the extent to which promotions for our company on the podcast website drive traffic to our main company site, using SQL like this:

SELECTreceived_at,context_page_url,context_page_referrerFROM`ra-development.company_website.pages`WHEREcontext_page_referrer LIKE '%drilltodetail%'AND context_page_url LIKE '%https://rittmananalytics.%'ORDER BY1

We also auto-track all page views, link clicks and button click events in a similar way to Heap and Mixpanel’s autotrack features, using code such as the example below injected into the footer section of all of our site page.

<

script

>

var

links

=

document

.

getElementsByTagName

(

'a'

);

for

(

i

=

0

;

i

<

links

.

length

;

i

++

) {

links

[

i

].

addEventListener

(

'click'

,

function

() {

analytics

.

track

(

'Clicked a Link'

, {

target

:

$

(

this

).

attr

(

"href"

),

title

:

document

.

title

,

label

:

$

(

this

).

attr

(

"innerText"

),

Link_text

:

$

(

this

).

attr

(

"text"

),

baseURI

:

$

(

this

).

attr

(

"baseURI"

)});});};

</

script

>

As well as using Segment Connections to route customer and visitor data from our website and other sources into our downstream marketing applications, we’ve also started to use Segment Personas to build-up a 360-degree view of each visitor’s interactions on our site and score those visitors by their potential to become a sales lead.

We do this through two features that Personas provides; computed traits and SQL traits. Traits are properties that we assign or compute for visitors to our site and computed traits allows us, for example, to calculate a running total of how many non-podcast and non-homepage pages that a visitor has looked at on our websites.

Computed traits can be counts of certain event types filtered on a property value; aggregations (sums for example) of revenue values in transaction events, unique lists of event property values such as unique podcast episodes and can be calculated over a sliding window of days, in our case 30 days.

Individual computed traits can then be combined in more complex calculations together with external data in SQL traits, such as the one we use to calculate our engaged prospect score.

Finally, we can define an audience in Personas based on this engaged prospect visitor score that includes all visitors with a score above a certain value based on their last 30 days activity.

This audience is then made available for sending to downstream destinations along with other audiences based on individual computed trait conditions.

You can read more about our partnership with Segment here, or schedule a call with us now if you’re interested in building-out a customer data platform or using Segment Personas for this type of scenario.