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DECODING &
DEMYSTIFYING
DATA INTEGRATION
MICHELE KISS
Partner, Web Analytics Demystified
michele@webanalyticsdemystified.com
WEB ANALYTICS DEMYSTIFIED

We literally wrote the book(s) on digital analytics!

@michelejkiss
Remember the good ol’ days?

@michelejkiss
@michelejkiss
The consumer journey

@michelejkiss
@michelejkiss
@michelejkiss
@michelejkiss
Decoding & Demystifying Data Integration
Decoding & Demystifying Data Integration
Decoding & Demystifying Data Integration
Decoding & Demystifying Data Integration
Decoding & Demystifying Data Integration
@michelejkiss
@michelejkiss
Inconsistent user experience...

@michelejkiss
@michelejkiss
@michelejkiss
“What can I do?”

@michelejkiss
@michelejkiss
@michelejkiss
@michelejkiss
@michelejkiss
@michelejkiss
@michelejkiss
DATA INTEGRATION EVOLUTION

@michelejkiss
Siloed marketing
views and
reports:

Integrated views:

•Website
•Email
•Social

success

•Understanding the

•KPI measurement

individual across
channels

•Campaign/initiative
across channels

Customer as the
common identifier:

•Comparing trended
data across channels

@michelejkiss
Siloed marketing
views and
reports:

Integrated views:

•Website
•Email
•Social

success

•Understanding the

•KPI measurement

individual across
channels

•Campaign/initiative
across channels

Customer as the
common identifier:

•Comparing trended
data across channels

@michelejkiss
@michelejkiss
“Just pull all the data in, then we’ll figure it out”

is not a strategy

@michelejkiss
@michelejkiss
DON’T THINK ABOUT METRICS.
START WITH GOALS AND OBJECTIVES.
(Metrics for metrics’ sake are worthless. )

What are the overall business goals?
What are the goals of this effort?

What do you WANT?
How will you know if you got it?

@michelejkiss
@michelejkiss
Defining what’s important is more work up front, but it
gives you the structure to know what to bring in.

@michelejkiss
DEFINE KPIs
This isn’t a list of
“every metric we can think of to
put on a report”
or “every metric I can pull out of
Google Analytics”

These critical metrics will be used
to determine success.
They define what you want out of the effort.
@michelejkiss
Business Objectives

Measurable KPIs

@michelejkiss
IDENTIFY YOUR SOURCES
You’ve determined your KPIs...
•What data sources do they come from?
•How can you access?

@michelejkiss
Does the data exist?

@michelejkiss
Does the data exist?

1. Does it exist at all?

@michelejkiss
Does the data exist?

1. Does it exist at all?
2. Does it exist in the tools you have access to?
@michelejkiss
Does the data exist?

1. Does it exist at all?
2. Does it exist in the tools you have access to?
3. Does it exist in the format you need?
@michelejkiss
METHODS OF ACCESS
Direct Connector

Direct Connector

Excel, Access or Text file
Google BigQuery, HIVE,
ODBC and more

@michelejkiss
BRING IT ALL TOGETHER
Campaign Goal: Engage consumers and
drive purchase via photos, sharing and coupons
KPI

Goal

Coupon Prints

Purchase
intent

20,000

25,000

125%

Coupon
Redemption

Purchase

15,000

12,500

83%

Photo Submissions Engagement
on microsite

50,000

49,000

98%

Facebook Coupon
Shares

18,000

25,000

139%

Awareness

Target

Actual % to Goal

@michelejkiss
You’ll still dive deeper…

@michelejkiss
Forest, not trees

@michelejkiss
@michelejkiss
Questions?

M ICHELE KISS
Partner, Web Analytics Demystified
michele@webanalyticsdemystified.com
@michelejkiss

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Decoding & Demystifying Data Integration

Editor's Notes

  1. So before we begin, a little about us. Web Analytics Demystified is the global leader in digital analytics consulting. When I say that we “wrote the book on digital analytics”, that’s not hyperbole. We literally did. Web Analytics Demystified and its Senior Partners co-founded Web Analytics Wednesday and the Analysis Exchange (which teaches beginners how to do web analytics, while helping non-profits), penned the Web Analyst “Code of Ethics”, and our senior partner John Lovett is President of the Digital Analytics Association. My focus at Web Analytics Demystified is our analysis and analyst mentoring practice. This means I not only help our clients with hands-on analysis, but I also work with them on how to succeed at analysis as an organisation, from building the right team to providing the right education and training to growing their people and their practice. So, a lot of these challenges - how do I bring together data? How do I create a cohesive view of our efforts? - I deal with on a daily basis.
  2. Those working in marketing and analytics these days might remember the “good old days” What we now call “digital analytics” was called “web analytics” - because the website was really the only true digital channel. Sure, online and offline was a challenge even back then, but it was a simpler one.
  3. Now, social media, mobile, tablet and multiple-device behaviour, have made the consumer journey more fragmented - which means analytics has gotten more complex.
  4. Today, brands of course still have a website. But they’re surrounded by an entire digital ecosystem. And sometimes, depending on the brand, the business model and their marketing plans, this ecosystem can be more important than the website itself. A brand may have Facebook ... and YouTube ... and Twitter ... and Pinterest ... and iPad apps ... and iPhone apps .... And looking at just “web analytics” isn’t enough to judge marketing success any more.
  5. Today, brands of course still have a website. But they’re surrounded by an entire digital ecosystem. And sometimes, depending on the brand, the business model and their marketing plans, this ecosystem can be more important than the website itself. A brand may have Facebook ... and YouTube ... and Twitter ... and Pinterest ... and iPad apps ... and iPhone apps .... And looking at just “web analytics” isn’t enough to judge marketing success any more.
  6. Today, brands of course still have a website. But they’re surrounded by an entire digital ecosystem. And sometimes, depending on the brand, the business model and their marketing plans, this ecosystem can be more important than the website itself. A brand may have Facebook ... and YouTube ... and Twitter ... and Pinterest ... and iPad apps ... and iPhone apps .... And looking at just “web analytics” isn’t enough to judge marketing success any more.
  7. Today, brands of course still have a website. But they’re surrounded by an entire digital ecosystem. And sometimes, depending on the brand, the business model and their marketing plans, this ecosystem can be more important than the website itself. A brand may have Facebook ... and YouTube ... and Twitter ... and Pinterest ... and iPad apps ... and iPhone apps .... And looking at just “web analytics” isn’t enough to judge marketing success any more.
  8. Today, brands of course still have a website. But they’re surrounded by an entire digital ecosystem. And sometimes, depending on the brand, the business model and their marketing plans, this ecosystem can be more important than the website itself. A brand may have Facebook ... and YouTube ... and Twitter ... and Pinterest ... and iPad apps ... and iPhone apps .... And looking at just “web analytics” isn’t enough to judge marketing success any more.
  9. Today, brands of course still have a website. But they’re surrounded by an entire digital ecosystem. And sometimes, depending on the brand, the business model and their marketing plans, this ecosystem can be more important than the website itself. A brand may have Facebook ... and YouTube ... and Twitter ... and Pinterest ... and iPad apps ... and iPhone apps .... And looking at just “web analytics” isn’t enough to judge marketing success any more.
  10. Today, brands of course still have a website. But they’re surrounded by an entire digital ecosystem. And sometimes, depending on the brand, the business model and their marketing plans, this ecosystem can be more important than the website itself. A brand may have Facebook ... and YouTube ... and Twitter ... and Pinterest ... and iPad apps ... and iPhone apps .... And looking at just “web analytics” isn’t enough to judge marketing success any more.
  11. Today, brands of course still have a website. But they’re surrounded by an entire digital ecosystem. And sometimes, depending on the brand, the business model and their marketing plans, this ecosystem can be more important than the website itself. A brand may have Facebook ... and YouTube ... and Twitter ... and Pinterest ... and iPad apps ... and iPhone apps .... And looking at just “web analytics” isn’t enough to judge marketing success any more.
  12. Understanding the success of your marketing efforts now involves a wide range of solutions, which (for far too many companies) typically live in silos. Website data Mobile data CRM data Social data Consumer feedback data Optimisation and testing data ... and more. In fact, it actually looks a little more like this...
  13. Oh yeah, and did I mention? All these sources have their own UI and their own way of displaying (and even exporting) data. No wonder marketers can’t get a comprehensive view....
  14. Early on in my career, I remember attending conferences and hearing speakers lament about best practices of data integration and why it was so critical. However, I remember sitting there as an analyst thinking, “I know this. I know it’s important. But oddly enough, I don’t have a couple million to fund this for my company, or the clout (yet) to argue for it. <<CLICK>> What can I do?!”
  15. Early on in my career, I remember attending conferences and hearing speakers lament about best practices of data integration and why it was so critical. However, I remember sitting there as an analyst thinking, “I know this. I know it’s important. But oddly enough, I don’t have a couple million to fund this for my company, or the clout (yet) to argue for it. <<CLICK>> What can I do?!”
  16. I’m definitely not alone in this. Analysts have been taking matters into their own hands for some time now, typically leveraging tools like Excel plugins or APIs to bring together data from multiple sources. However, while Excel is (sadly) referred to as the “most common business intelligence solution in the world”, it can fall short of delivering what analysts and marketers really need.
  17. So when new solutions are available to put control in the hands of marketers and analysts, and not require multi-million dollar investments, this is great news. It’s why I was so excited to first try Tableau’s (then beta) connection to Google Analytics. (So much so that I was playing with it on my Christmas vacation in Australia!)
  18. It’s easy to get overwhelmed when starting this process, but it’s also important to keep in mind that this is an evolution - and it’s okay to grow into it. At your first pass, you’re not even thinking about trying to get to a completely integrated system involving cross-channel and CRM data! You’re just trying to bring different sets together into one view.
  19. There are three stages of maturity when it comes to cross-channel analytics and integration. 1. Disconnected (or siloed) data 2. Comparison and correlation of data from multiple sources, which is our primary focus today <<click>> 3. True “person”-level integration of data across channels “Person” level data integration requires significant corporate investment in people and technology to integrate data by a common key: the individual. However, it’s much more than just “shoving data into a datawarehouse” - there are some fundamental challenges. For example, my Facebook account in no way ties me to my Twitter user ID, nor allows a company to understand me according to a Google Analytics User ID. Certainly, that kind of truly comprehensive view of the customer is “the dream.” It can be tempting for marketers to see centralisation of data as a cure to all their analytical ills. But haphazard data integration will actually create more problems than it solves! That’s why we need to <<click>> STOP.
  20. There are three stages of maturity when it comes to cross-channel analytics and integration. 1. Disconnected (or siloed) data 2. Comparison and correlation of data from multiple sources, which is our primary focus today <<click>> 3. True “person”-level integration of data across channels “Person” level data integration requires significant corporate investment in people and technology to integrate data by a common key: the individual. However, it’s much more than just “shoving data into a datawarehouse” - there are some fundamental challenges. For example, my Facebook account in no way ties me to my Twitter user ID, nor allows a company to understand me according to a Google Analytics User ID. Certainly, that kind of truly comprehensive view of the customer is “the dream.” It can be tempting for marketers to see centralisation of data as a cure to all their analytical ills. But haphazard data integration will actually create more problems than it solves! That’s why we need to <<click>> STOP.
  21. Think of the plethora of data available in just ONE analytics tool, and how bloated typical web analytics reports can easily get. (Especially when we get in to the situation of: “Hey can you add this? And this? And show both week over week and month over month?”) When we talk about integrating data from a number of different sources, we take that and multiply it by 3, 5, 10, even 20. Unfortunately, MORE data doesn’t lead to more insight if you can’t separate what’s important. To integrate data successfully, we need planning and strategy. We need a cross-channel measurement plan. .
  22. “Just pull in all the data and then we’ll figure it out” is not a strategy. Creating a cross-channel measurement plan is a critical step, prior to actually integrating data.
  23. Having a plan will help you: Make sure you include the right data Don’t waste time bringing in the wrong data Don’t bring in too much (unnecessary) data, and overwhelm people Have clearly established goals - and, therefore, Have clearly defined measures of success This requires a conversation (or several) between your marketers, who own the business goals and actions, and your analysts, who ultimately need to report on success. .
  24. DON’T think about metrics. I know, ironic for analytics person to be saying this. But that’s because your metrics have to be fueled by something, and we need to start there. Metrics for metrics’ sake are worthless. What are the business goals? What are the campaign goals? What do you WANT? And how will you know if you got it? (I call this the Fired or Promoted test. What results would have you running scared if called into your boss’ office? And what results would have you calling the BMW dealership?) It is critical this happen AT THE START. This isn’t a last minute “after all the results are in” - this is core to planning the campaign itself. So, it’s important to think ahead and define ...
  25. Defining what’s important is more work up front, but it gives you structure to know: 1) What data to you need to bring in 2) Set concrete goals around that data 3) Not waste time on irrelevant data that doesn’t add to insight (and typically just seeks to confuse the picture)
  26. This process involves defining the KPIs for your initiative. Too often, people forget what the K in KPI stands for: KEY Performance Indicators. Hint: If you have 85 of them, I can bet you they are no longer “key” It’s also how you end up with 45-page “KPI Reports” (no, not kidding) These need to be CRITICAL “pop the champagne” or “uh-oh I hope I have a job on Monday” metrics. This isn’t a list of “every metric we can think of to put on a report” or “every metric I can pull out of Google Analytics” These critical metrics will be used to determine success. They define what you want out of the initiative, and should be the most important pieces of data you bring in. That’s not to say that there isn’t other, supporting information that’s important for the complete picture. But you need to start with “critical” and work towards “informational”
  27. The KPI definition step is a critical link between BUSINESS OBJECTIVES and DATA. If your goal is “awareness” (a commonly spouted, but incredibly fuzzy, goal), how do you define that, and how are you going to measure it? It takes your GOALS and translates them into something MEASURABLE.
  28. Now that you have established KPIs for the initiative, you need to figure out where this data will come from. Which often involves a critical question...
  29. Part of this process is verifying that the data you want EXISTS! This includes - Does it exist AT ALL? ….
  30. 1) Does it exist AT ALL? This might sound like a silly comment, but it’s not uncommon for marketers to have goals of reporting back the number of people who first saw a Facebook post, then browsed on mobile then purchased in store. Apart from obvious privacy considerations in that example, the data to understand that simply doesn’t exist! As my partner, Tim Wilson, aptly put it: Analytics can’t defy the laws of physics. If the data doesn’t exist, the data doesn’t exist. And unfortunately, with the proliferation of social channels, it’s even more increasingly common for new channels to emerge that aren’t accompanied by analytics (yet), or if they are, they are woefully rudimentary.
  31. 2) Does it exist IN THE TOOLS YOU HAVE ACCESS TO? Often times, getting insight you need may require leveraging additional toolsets. For example, social networks like Instagram aren’t known for providing robust data, but brands can sometimes tap in to third party (paid) tools for insight. But these, of course, require knowing that you need them in advance! (Which is why this pre-planning process is so important – so we identify this in advance.)
  32. 3) Does it exist IN THE FORMAT YOU NEED? It’s easy to assume that if the data exists, that you can leverage it in its current form. However, especially with a lot of the newer social channels, data may exist but not in a way that is useful. For example, let’s say you’re running a campaign which spans channels including Instagram, and you want to know the number of photos using a certain keyword. Being able to manually go to the Instagram site, search for that keyword and COUNT the number of photos is not the format you need for campaign measurement.
  33. Depending on your data sources, there may be different ways you can access these to integrate. Sources like Google Analytics and Salesforce have direct connections to tools like Tableau, but it doesn’t mean you’re limited to just that. By leveraging Excel, Access, Text files, databases and more, you can combine data from any source, in whatever way is easiest for you.
  34. Data integration allows you to pull together the success of an entire initiative in one view, even though it may span multiple channels. For example, let’s say you’re running a campaign that involves using coupons to understand purchase, and photo sharing to engage consumers. You use coupon prints to measure your goal of driving “purchase intent” You measure redemption to understand actual purchase You measure engagement via how many consumers submit photos on the campaign microsite And drive social awareness by encouraging and measuring sharing of the coupon via social channels. Data integration allows you to view how successful the pieces of that campaign were. It’s about having one comprehensive view of the success of your initiative. What were the goals, what were the KPIs, did you meet them (regardless of channel.) It’s about marketers not having to sift through fourteen reports to answer the question, “How did I do?”
  35. That’s not to say this is the only information you’ll ever need to look at, or that there is no need for deeper analysis and insights into individual channels. There is, and there will be. You’ll want to deep dive into specific channel performance, and marketers will always want to know more. After all, there’s a reason that so many different analytics tools exist. There is no one tool that allows you to full explore every intricacy of every channel. It’s appropriate to have an integrated channel view, plus an in-depth channel focused view.
  36. But this allows you to see the forest. Because ultimately, success is not judged by the pieces, but by the whole.
  37. Questions?