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Google Analytics

Conversions are down. Data you need to analyze to avoid it.

November 25, 2016

Are you panicking because your website is driving fewer sales or conversions? The first thing you’ll need to do is open up your analytics tool and start digging into the issue. This article will talk about some of the key things to look for when your website stops performing.

What to consider when you look at your web data is the fundamental of the web performance equation. The equation is:

[Traffic x Conversion Rate] x [AOV] = Revenue

Traffic x Conversion Rate = Orders
Orders x AOV = Revenue

This is a pretty universal equation for digital marketing and e-commerce.

If your problem is that the revenue is declining, then you’ll need to take into account of the AOV (average order value) impact.

Let’s start looking at the impact of the key metrics, and see how we can diagnose the issue breaking it down by ‘traffic’ and ‘conversion rate’.

Conversion drops because of lower web traffic

One main reason your orders are down is due to the fact that the site’s traffic is down. Traffic of your website could be impacted by many things, but if you’re in Google Analytics or similar tool, the first thing to look for is what traffic source you’re seeing the decline is coming from.

Look into channel report and see which bucket of traffic is declining. Then Look into which source and medium are causing the traffic to decline. If you’re paying for advertising, look into if there is any issues with your ads or campaign set up.

ga-sourcemedium-112016
Google Analytics traffic source report.

There will be times where traffic sources aren’t an issue as overall traffic is not down at all. In that case, you’ll need to look at the traffic from the perspective of user behavior. If you have a marketing funnel, then look at the funnel and see if there are any major changes in traffic within the funnel.

In Google Analytics you can use the reports within Behaviors and Conversions section. Start looking at the traffic pattern and see if you have any traffic drop off that could be impacting the traffic going into your cart. That would definitely lower your conversion rate and a number of orders.

Conversion drops because of lower conversion rate

In your web analytics tools like Google Analytics, you would usually set up goals that you want to track. When you set that up, usually the tools is able to start reporting on conversion rate (# of goals occurred divided by the traffic). Using this conversion rate metrics, you can use that to see if particular sources of traffic are causing a lower conversion rate. Usually, you’ll compare the data from different date ranges, like a month over month, or current week vs. last week and such.

Some the key reports to dig into where the conversion rates are dropping is.

  • Funnel report
  • Goal flow
  • Channel and source/medium report
Google Analytics Goal Flow report
Google Analytics Goal Flow report

These are the basic reports, but sometimes you make changes to websites (i.e. adding a link that may take away users to another page away from shopping cart or flow). In such case, you need to dig into if people are going from certain page to another page. In such case, you can use the Behavior > Site Content > All Pages, and chose a page and look into Navigation Summary. If you see that more people are going away to another page that doesn’t matter than you may have an impact and explanation to why your conversion rate is dropping.

ga-funnel-112016

Average order value (AOV) is declining

When you’re looking at the revenue decline, and realize traffic is not declining, and conversion rate hasn’t changed, then you may have a decreasing AOV. When you’re AOV is declining, the number of orders is decreasing, and that could mean few things.

  • People are ordering items at a lower price point
  • People are using promo/discount codes more so than prior weeks
  • People are buying fewer number of items within a transaction

More people are visiting a product page with a product at a price point fewer than the average price sold
In many cases, this issue is less about your website unless the traffic is lead to a page with the product at a lower price than average.

 

So hopefully, this gives you a basic understanding of how you could approach analyzing data once you start seeing the conversions go down.  Don’t panic, just go into your web analytics tool like Google Analytics and follow the steps I mentioned above.  More advanced users will look into more strategic and tactical things, but this is probably a start.

Great analysis goes further to explain WHY

April 11, 2015

A lot of the data analysis revolves around the business questions that people bring to you. Horrible questions are like when analytics people gets a simple data pull type of requests, but no background information or explanation of why they would be needing a data. Hopefully, that is the not the case for you, and we hope to believe in a perfect world where all marketers and business folks are asking great business questions.

Typically, marketers are trying to achieve something out of their marketing efforts, and we (analysts) are trying to meet their needs by providing data and insights back. A lot of times what’s lacking in this analysis or the challenges from the marketers lack the awareness of probing into the ‘why’ factor in the change in the data trend.

What does this mean?

For example, when paid search traffic goes down, a typical analysis would look at the traffic, ad spends, it’s associating pages, the list of keywords, conversion rate, etc. Usually, great analysts go far more because awesome managers, executives, and business people ask challenging questions. That means, showing ad spends going down or conversions going down is not just enough, they’ll ask “why” several times.

Heavey web analytics users will find over time that just using Google Analytics alone will not give you the answers you’re looking for.  Here are few ideas to use help you get better underlining reasons to why things go up or down in traffic.

Segmentations, filters, drill down and add columns

Use macro data like Google Trends, Webmaster Tools, etc.

Look at competitor’s data

Use surveys

Perform A/B testing

Segmentations, filters, drill down, and add columns

As an exampleHere is a sample view of the detail filters and segmentations you can build our of google analytics. Segment generation is a pretty powerful feature as you can create a rule that applies to your entire reports and compare. The segment applied is sticky so you don’t have to always have to think about adding when you switch between reports. Much other analytics tools has a similar feature, but it is something you have to take advantage of.

ga-traffic-segment-042015

 

The segment could be a cumbersome feature especially if you want to play around to quickly find something that sticks out. The secondary dimension helps you quickly add a column, so you can sort and compare by different date range. Typically that could give you something interesting that explains more details in your data trend.

ga-traffic-2nd-dimension-042015

 

Here is a basic filter feature within google analytics, but it is pretty helpful when you want to exclude or include certain data sets so that you can narrow down to particular data that may explain the cause of the traffic changes

ga-traffic-filter-042015

 

Use macro data like Google Trends, Webmaster Tools, etc.

Checking out data on Google Trends and many other market data could give you a broader sense of what could be happening.

A hypothetical example here:  Despite allergies, queries are going up peaking at April/May, yet the search on major allergy relief pills brands are flat?  What’s happening here? Is something taking away your search/interests share away?  Are natural remedies growing?  Definitely a good context of data if you want to look at a more higher level explaining traffic trends.

google-trends-allergies-042015

 

Look at competitor’s data

Site’s like SpyFu (note: there are many other similar tools out there), allows you to see what’s happening on site’s that you don’t control. Let’s take a peek at Nike golf site. They’re kicking ass in branded terms in Organic Keywords, no surprises here. But it looks like in Paid Keywords, you’ll find ‘Callaway gold drivers’ as one of term Nike is bidding on.

It is pretty common for brands to buy competitor’s terms to steal traffic or interests. Idea is to watch out of potential changes in competitor’s marketing strategies because that could explain changes in your traffic or business performance.

spyfu-competitor-sem-042015

 

Use surveys

I’m a big fan of Qualaroo because it gives me that flexibility to whip out a quick survey to place on a page and control the survey introduction timing. It helps us ask site visitors directly and answer potential questions that quantitative data that Google Analytics couldn’t answer.

I won’t write much about this because it is pretty no-brainer, but this is some powerful stuff if you ask the right questions. I like using the open text questions and take advantage of that initial insights to help me structure better questions next time.

voc-qualaroo-042015

Perform A/B testing

The reason why we test is because “We don’t know what the outcome is going to be”. You can spend in a meeting room all day, but at the end of the day, you are not going to know if it is going to work. Go test it out!  Tools like Optimizely will allow you to whip out some basic A/B testing on the site.

If setting up A/B testing and putting that JS code is too much for you, then try tools like UsabilityHub.com. You can basically test your idea during your conception phase by asking users to perform some action to get data. You can link your existing page and ask users to perform certain tasks. See if your site sucks or does its job.

userbilityhub-jira-example-042015

How to Analyze Mobile Metrics

June 29, 2012

You hear a lot about mobile metrics in digital marketing. When I was at the Think Shopper event at Google, they emphasized on investing in mobile. According to their insights, in the US, only 33% of advertisers have a mobile optimized website. There is clearly a huge gap between in actual consumer behavior and what companies are delivering online. It seems to me marketers aren’t seriously looking into mobile and executing on the insights.

So here is my few metrics scanning technique to quickly understand the signal from what is consumers are telling you about consumer journey or their experience on your site via mobile (in this case includes tablets). When companies don’t have a marketing plan, objective, goal… they usually ask analyst on what’s happening with traffic. What’s the current state?, blah blah.

I hate analyzing data without objectives and goals, but in reality, this is part of the job of analysts. Please remember that data analysis is as good as the business questions. When there are no good business questions to answer, then think of business questions you think fits the business then formulate the answers to answer those questions.

In such data analysis exercise, we still need some kind of tactical approach to understanding mobile. These are ideas, but I’m also attaching my rationale behind it. Additional ideas are welcome.

Here is the outline of the key analysis points
– By how much is your mobile traffic growing? (questions the relevancy of mobile traffic to your business)
– What is driving the traffic (questions where to potentially invest more or less based on current traffic drivers)
– Are mobile users consuming the content differently (questions where and what to optimize or create content strategy)
– Difference in interaction or task completion, mobile vs. non-mobile segment (questions if your mobile site is working or not)
– Time factors, recency, and frequency (questions if your mobile is driving loyal or engaged audience)

By how much is your mobile traffic growing?
This is an obvious one. Given that many research papers are talking about the growth of mobile and it’s internet access, how is your website doing? My piece of advice doesn’t expect your mobile traffic is growing according to the industry or market trend. One of the things I’ve noticed is content catered to mobile has done a lot with how your website’s organic reach to mobile users (content in either a form of content written about mobile, or page that is mobile optimized). * note organic, because companies do pay for ads targeting to mobile…

Make sure to look for signs that could possibility drive higher growth rate. In most cases the mobile traffic growth is not just happening naturally, it could be those content you’ve written or syndicated somewhere.

Mobile Traffic Growth YoY

So as you can see, my blog’s mobile traffic growth is pretty significant looking at year on year. My blog traffic is very small, but imagine you see that growth in your company’s website. That growth is something. What percentage of traffic share does it represent? You might want to check that out by year over year. I’ve noticed 2010 to 2011 has shown significant growth particularly from tablets (iPad in particular). What about your website?

What is driving the traffic
Things you need to look for is traffic sources and the actual pages driving the mobile traffic growth. Would it be the inbound traffic to a website or would it be some content specifically in interests to mobile users’ journey online?

Again, an example from my data.
Sample Mobile Traffic Sources

Wow, so Google is really helping me drive mobile traffic to my blog and year on year, it is driving a pretty significant percentage increase as well as volume (blurred). MR. Avinash’s Occam Razor blog is also driving some good lift in mobile audience year on year for my blog.

So given that search is driving traffic, it is a good timing to look at the content that people are finding via Google SERP. So go to content and segment by organic search. You’ll see which page is really giving you that organic traffic from mobile.

Are mobile users consuming the content differently
Don’t expect the mobile user to stay on your website as long as PC browsers. Remember that most likely the mobile users are swiping their fingers and clicking rapidly through various content. Also in their consumer journey, mobile users could physically be in different places from traditional PC environment Hence, consumer mindset on what info they need and expectation from their activity online are very different from traditional PC environment.

Review mobile segment vs. non-mobile segment, and look at page views per visit, bounce rate, time on site, and recency & frequency. This will set the tone on setting up a different digital marketing strategy for mobile, in both traffic acquisition, and usability of the website.

Difference in interaction or task completion, mobile vs. non-mobile segment
Do the same with the previous point on content by looking at mobile vs. non-mobile segment. The difference is to make sure you obsess about understanding the difference in task completion rate behavior pattern on mobile vs. non-mobile users. Task completion could be anything on conversions such as file downloads, newsletter sign up, sales conversion, add to cart, watched a video, etc.

This part of the analysis is very important. Your website exists for a certain reason, hopefully not just to drive traffic, but to drive some outcome that adds value to both your customer/consumer or business. Obsess in analyzing mobile users against conversions.

Random ideas to look for in this exercise…
– Recency & frequency for mobile converters, to look for differences in customer journey pattern
– Landing page difference for converters and page value
– Multi-channel attribution on mobile segment vs. non-mobile segment
– Conversion rate analysis by traffic sources
– Customer profiling on mobile converters vs. non-mobile segment (age, gender, etc.) Yes, you can do this if you have your analytics integrated with social graph

Time factors, recency, and frequency
I’ve kind of touch this in the previous point but keep in mind that smartphones are with consumers 24-7. It is personal, and they may have apps they frequently use to access blogs or get notifications on a phone while in their pocket to read things.

As you can see from my recency or ‘day since past last visit’ shows 2 days apart traffic shows a higher traffic distribution on this bucket than a non-mobile segment. My blog traffic is obviously going to be different from your site, so check out to see if you are getting some interesting results. It is probably more likely that users on mobile ar revisiting your website more frequently given that you’re adding content occasionally.

Mobile Traffic Recency

Analytics solutions like Mixpanel can also perform cohorts analysis, so you might find your traffic has a better recency conversion from one event to another event (i.e. free signup to premium account signup). Eyeball the time factor in conversion really closely, mobile customer journey is very different from traditional PC behavior so you might find different insights leading to a whole new digital marketing strategy.

Hopefully, you can find something interesting about your consumers or customers on smartphones. Have fun analyzing!!

Google Analytics Multi-Channel Funnels Report

October 23, 2011

Here three reports that are very interesting within Google Analytics which gives great visibility around multi-channel funnels reflecting various path website visitors take.

  • Multi-Channel Funnels > Top Conversion Paths
  • Multi-Channel Funnels > Assisted Conversions
  • Attribution

In my view, Top Conversion Paths and Assisted Conversions under multi-channel funnels reports are interesting.

I will focus the on the multi-channel report for this post. It is pretty revolutionary as many data analysts always wanted this type of data to understand how much marketing channels or traffic sources actually contribute to sales.

A lot of these type of digital channels may not directly close sales, but could assist sales. So getting that data visibility is really awesome!

The multi-channel funnel report allows marketers to understand the popular combinations of paths users took within digital channels to arrive at your tracked website. It is pretty cool because you can filter the channels by medium, keywords, custom group sets, etc.

 

Google Analytics Multi Channel Funnel

Are the ads driving top of the funnel traffic or attributing to last touch conversion

This report shows you that certain channel like Referral and Display Ads are more likely to assist another channel in sealing the deal.  In other words, if you’re tracking last touch attribution only channel like Display Ad where you are spending money may not be getting the credit it deserves.

This is a great report that tells you if you have any reporting attribution issues.

Google Analytics Multi-Channel Funnels Assisted Conversions

 

Deep analysis around conversion segments.

As you may now, your site may be all about to drive sales, and it could have email registration or some kind of feature to drive leads. How does the user’s channel paths differ when the first interaction is Email or when Email is the last interaction?

If you know the leads you bring into promotional programs are likely to convert more and buy repeatedly, then it is worth exploring to see if there are any marketing opportunities to help consumers go down the marketing funnel.

Top Conversion Path Report

This is another powerful report to check.  In this example, I searched for any path that includes ‘Display’ Ads as their path to conversion.

What is interesting is that the top path that includes Display in their touch points show Display channel are likely to be either in the first touch or within the middle prior to the last touch channel that is not a Display Ad.

This is a great data that all paid media manager should be checking out.

Google Analytics Multi-Channel Funnels Top Conversion Path Report

Time lag report

One of the reports has the capability to understand the time difference (in days) between the channel path. If there are any opportunities you can intercept with an ad to close the sales, then I’m sure this report can give you that hint about the best timing to shoot and ad to make those days shorter.

Same goes with the path, if any channel segments are closing the sales in shorter path length, then it is probably worth diving into the data to see what is actually closing it.

Sample Time Lag report with segments applied.
Google Analytics Multi Channel Funnel

Integrating CRM With Digital Marketing Analytics Data

April 17, 2009

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

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