Integrating CRM With Digital Marketing Analytics Data

Kris
Kris

Table of Contents

I had to create a post talking about this wonderful article from Justtin Cutroni (@justincutroni)at epikOne.
Justin posted an article on March ’09 — Integrating Google Analytics with a CRM

Basically, there is a configuration you can do on javascript so that you can capture Google Analytics values and throw it into forms, CRM, or other areas of datasets.
According to his explanation, you have to use javascript to extract data from Google Analytics, store it in hidden form elements, and attach it to the form when users hit that submit button.
Why this is a great idea? Well, a lot of simple sites, including my my site have a contact form, but it only parses the data entered by the users and other necessary values to make the parsing work properly (behind the scene).

Taking my contact form as an example, it only captures “Name”, “E-mail”, “Interest”, and “Comments”. Now with Justin’s suggested configuration, you can pass along various Google Analytics values:
– Source (Possible campaign sources are Banner ad, Search PPC, Link Exchange, Newsletter, etc.)
– Medium
– Term
– Content
– Campaign Name
– Custom segmentation
– Number of visits

Wow… ok, what this means to me or you is that you can optimize the contact form to acquire not only the values we asked from the users, but all of these values from Google Analytics.
That means on an individual level, for example, I can tell Mr. ABC came from Google PPC, with the term “web analytics specialists”, and had 4 visits before contacting me.

Some may say, you can do that in the Google Analytics tool. Well, you got to slow down and be careful about that comment. Note that it is against the Google Analytics terms of service to capture individual identity information.
That is why it is nice to see that Google Analytics data integrating directly to forms, emails (in my inbox), into external CRM database, etc.

For those who are running enterprise level CRM suite, this is probably a joke considering that those CRM solutions can dynamically capture way more data and perform segmentation. But for small sites, bloggers, or micro-sites running Google Analyitcs, I feel like this has opened a door to a new level of thinking in site tracking using Google Analytics.

More companies are integrating their backend CRM databases with Web Analytics user behavior data. This is really powerful stuff if you can get the data in your hands. This is not surprising for experts deeply embedded into the practice. I would assume CPG and some Pharma companies are the champions at this.

The value of web analytics and CRM integration is enormous:
1) Web Analytics do not have people/customer data
2) CRM databases do not have web traffic behavior data

That said, we need both to tie user behavior or intent to who they are. Instead of going down the road of the ‘How To’ discussion, let me share you some ideas I’ve learned from Webtrends Engage conference. First, these data attributes are great start to consider to segment on once you get your integration in place.

Interest (online data)
Understanding intent is important, and we can obtain that through web analytics content reports. Example, users visiting support for product xyz are probably looking for a solution on that product. Pages report could be a powerful data when integrating with CRM.

Recency (online data)
How recent they visit the site could definitely tell you how urgent and the level of interest the users are on your service or product or value proposition. More recent users re-visiting the product page could mean that they are dying to know more or wanting it. Who are these people? You need to tie that data with CRM data.

Relationship (offline data)
What is the relationship with these users visiting your site? Customer who bought the product, or just contacted to learn more about future product? Your biggest customer maybe? Got to know their relationship to your brand.

Location (offline data)
Location could link to their user profile or even marketing effort. Did this customer bought your product during TV Ad period that ran in his/her city? Location could also represent character traits about the people living within that area. There is a reason why certain people live near the ocean vs. the mountains. It is good to know the context of the users from location stand point.

Demographics (offline data)
Ultimately you want to target marketing efforts to the folks that worked or did not worked. Who are they? Male/Female, particular age groups, etc. This will help understand how these demographic segment is behaving on your site. Very powerful ingredient to the analysis.
What data attributes you choose would depend on the outcome you are trying to analyze against. If it is sales, we need to think about different influences that will make your analysis more effective and bring insights/recommendations. Here are some ideas I got from Jason Burby from ZAAZ that highlights the priority and focus on where to assess.
1) Direct Purchase
2) Indirect, but identifiable
3) Likelihood to buy it
4) Educated estimates

This is very interesting because you can focus the analysis on these priorities where we could potentially make impact on controllable factors than the fuzzy factors like “likelihood”.

This is where segmentations come SUPER important. Segmenting on different data attributes would allow you to classify different behaviors and look at where most value is generated. Focusing on the controllable attributes are where you need to prioritize in your analysis.

Corporate and e-commerce sites sell products and services by providing information, and have the prospects register, so called “closed world”. Through various social network services, information are much more open and connected across the digital space now. This new “open world” is the new standard, and businesses are trying to figure out how to integrate the Social Media data and measure it’s value.

The majority of businesses host their consumer data in their CRM database. Typically, it contains information about their prospects and customers. Data ranges all the way from their profile, survey results, product registration, to customer support call history. In web anlaytics, more companies are investing in integrating online behavior data to CRM data base, so they could better target their marketing efforts and refine communication tactics. For example, reminding consumers to completely fill out the billing info to receive the limited offer. I don’t believe many companies are at the point where they’ve mastered this integration, yet hear a lot of people running around talking Social and Mobile data.

Web Analytics and CRM integration may be common now a days, and analytics solution provider should definitely focus and help businesses get this leg of the solution right. Creating robust segmentations around different rules against joined web analytics data and CRM data should be championed by a company before talking Social integration. The reason I say this is because Social Media data is about ‘people’, and if you don’t have your people database right, I doubt you’ll be able to effectively get the Social Media data integration right. Especially if you are looking at beyond mentions/buzz online and look at those people as part of your brand asset.

What’s missing from the new open world’s reality is that there are growing information about their potential customers online in social media platform, but discussion doesn’t extend to the most detail. Since the introduction of the Open Graph, now web sites and its pages are enabled with social capabilities that are trackable. Great example of that is the Facebook’s Graph API and Twitter API.

Communication and data are being passed from different page to page, sites to sites, platforms to platforms. Data could be pulled and it could also be pushed to update the other end of the authorized property. The challenge today is that these standards and best practices are changing very rapidly. What was open as a standard one day could not be a standard later (e.g. Facebook FBML), companies are being bought out by bigger companies, etc.

It is very important to identify the measurement framework, and identify long term data you want to implement to report as a metric or KPI (key performance indicator). I believe the important key things to think about on-boarding Social Media data are:

  • Who
  • Relationships & Connections
  • Outcome (including sentiments or qualitative results)
  • Time and Volume
  • Correlation

I’m still trying to figure out myself so it’ll be great if I can get some feedbacks and additional ideas.

Who
This is the obvious one. Social CRM needs to enable data to connect with who they are. Who is saying that your product is awesome, and who is liking your service? It becomes pretty important to study and learn how the Social Media service could provide your business with that data. One you have the capability to identify the people that matters to you, think and plan about getting that “segment” of data for you to analyze.

Relationships & Connections
One of the special thing about Social Media is its connection between people and services online beyond websites. Connection means there are communications between people and relationship is built on top of that connection rather it is bad or good. Everything you tweet and like on internet is tagged and identified somewhere in database and accessible through API. With that said, it is vital to think about how you could get that data correctly integrated into the CRM database or any other tools that allows you to segment and measure the Social Media’s value.

Outcome
When you here of “outcome”, it is tempted to hear ecommerce transactions or some event completion on the web site. In Social Media, it is important to think about the success or some outcome in a form like sentiments (good vs. bad), talking about product/brand/service, spreading the word, etc. It’s that action or behavior that you want to call it a moment of exclamation “!!”. Question is, can you identify and obtain such data, then integrate or curl that into your CRM data environment?

Time and Volume
Time factor is important in data, as you want to be able to see the trend and any positive or negative impact from particular communication or marketing online. Don’t assume the Social Media like Facebook would allow you to pull the entire historical data. In that case, you need to think about the granularity of data (daily, weekly, quarterly) you need and see if that is something you can get. Some social data when pulled will give you the “as of” that time, but may not be able to give you the trended data. Definitely need to ask if those identified KPIs are even available in time series.

Volume is part of the common data we’ll need to plot against time, basic stuff but wanted to call it out. For example, # of likes, comments, mentions, etc.

Correlation
It is pretty common for companies to correlate Social Media like mentions, re-tweets, or comments against website traffic or sales. Digital data plays a vital role in understanding the media mix. Basically to understand the best allocation of marketing dollars and gain the best return on investment. So what Social Media metrics will play that role in analyzing marketing mix. That said, pulling that data in a Business Intelligence warehouse would be an important factor to think about. CRM aspect comes into play because if you integrated that Facebook ID, Twitter ID with CRM’s people’s profile then your segmentation becomes more rich.

What this all means…
Now, assuming you get this all worked out, and all these Social Media KPIs are set and necessary data about the people are in Social/CRM database. Web Analytics solution plays a pretty important part in gluing the data together and create segments to take action. Not on all occasions though; it works especially well if your website is that core part of user experience towards bottom of the funnel or the property yielding the return. Some other factors why web site and analytics play a key part in the segmentation:

  • Your web site may be more measurable than any other online channels
  • Single point where all transactions occur
  • Primary property where CRM data and cookie data or session data or keys are created.
  • Studies show consumer trust corporate web site and great amount of sample data are available

Globally, corporate site plays a pretty important role and consumers do expect brand promisses from corporate’s web site. Web sites will still play a critical part of user engagement with the brand and in the new open world that could be a m.site, landing page from that twitter link, trusted property to opt-in for news letter, unique offers from the brand via their site, etc.

Once the Social CRM environment are set up and you’re able to tie your web analytics data with it, next steps are to segment the hell out of it and find valuable segment of audience or trends. I believe that’s where the insights would come from in this point in time of digital era.
Every companies have different business objectives, so ingredients to analyze cross data sets from web analytics and CRM data would be different. Hopefully these ideas I learned from the experts were able to spark some analysis ideas. :)

Shout out to following experts who have deep knowledge in this area who made this visible to us at the conference:
Gary Angel from Semphonic
Adam Greco from Web Analytics Demystified
– Responsys
– Jason Burby from Zaaz

Analytics

Kris

As a data journalist, I enjoy curating and analyzing marketing trends, and data. The things that fascinate me the most are the transforming business landscape due to evolving marketing technologies.