Digital Analytics

Tips to Move Towards Big Data & Enterprise Solutions Part 2

September 19, 2012 by Daniel Laws Leave a Comment

Last week, I released my Tips to Move Toward Big Data & Enterprise Solutions that focused on your organization internally. This week’s 5 Tips to Move Towards Big Data & Enterprise Solutions are focuses on projects and customer outcomes from the data.

1. Think Data Quality & Security

In this day and age, it’s critical that you think of data quality and security for the long-term. What’s the point of having data if it’s not worth a damn? Work to implement data quality testing and regular data quality checks to ensure that you’re collecting as well as filtering to the necessary databases or solutions.

With all of the privacy issues and customer concerns, you’ll need to create data security policies and procedures. I would advise that you openly display your data collection polices on your website as well. The IAB is a great resource to help you self-regulate online behavioral advertising and how you use data.

2. Start small with a project

Rome wasn’t built in a day and Cesar didn’t build it by himself, so start with small projects. This will help get departments to collaborate and build relationships. It will also help to identify issues that would adversely impact larger projects so that you can develop a plan to solve the issues. Small projects will be the building blocks of long-term solutions for big data and enterprise solutions.

In my experience, if you can show proof of a successful small project, it will help the decision-maker to see the value and provide justification for universal data as well as the implementation of enterprise solutions. Tie the small project to brand or high-level strategic goals and objectives, and it will improve your level of internal support.

3. Focus on High Value & Good Customers

The small projects should focus on high value customers. It’s recommended that you look to answer questions about high value customers, such as who they are, how they interact with your brands, what marketing tactics are critical to conversions, etc. Again, align this information back to your organization’s goals & objectives to gain internal support.

4. Focus on Insights & Outcomes

The high value customers generally account for a large part of revenues, so focus on insight and outcomes that align with revenue generation. Think about what causes high value customers to complete an action or task. Sometime that data can help you develop hypotheses that can later be validated with surveys or focus groups. It’s recommended that you connect the quantitative and qualitative data but it needs to be simplified so everyone internally can understand the value of the data.

5. Don’t Measure Everything, Measure what Matters to the Project/Customers!

I’d heard many people say, “Measure everything,” and I understand the thorough process behind it. If you’re looking to move toward big data & enterprise solutions, I would recommend only measuring what matters for your specific project. How do you ensure that you’re capturing the data that matters? It starts with a measurement plan that aligns goals, objectives and KPIs for your project.

Conclusions

This list of tip should help to get your organization on the path toward “Big Data and Enterprise Solutions” but it’s not the end all, be all document. It should get your thinking about internal, external, and the politics that comes with navigation across business unit to develop value for marketing and your customers. Let us know what type of progress your organization is making and send us your recommendations to expand the list.

Tips to Move Toward Big Data & Enterprise Solutions Part 1

September 12, 2012 by Daniel Laws 1 Comment

With all of the talk about “Big Data”, I thought it was about time that I provide you with a few recommendations to get your organization moving to leveraging large amounts of data. The beauty of having big data is that you can be statistically confident when testing. Small businesses don’t always have the luxury of this when looking to get a large sample size.

After years of working for organizations such as Liberty Mutual, Sovereign Bank, Idearc Media, and numerous clients (Comcast, Merck, Helzberg Diamonds to name a few), I want to share what I’ve learned about Big Data. Below are my top 10 tips for big data or developing enterprise solutions that can make a difference:

1. Leadership & Way of Life

You’ll need leadership that’s focused on the facts, invested in people/technology, and constantly pushing for better customer value. At this time, leadership will need to put up or shut up every step of the way. Prove it to your customers and employees with actions based on big data that’s part of the organizational goals & objectives!

2. Integrate and Simplify Solution Platforms

Simplify and integrate solutions for optimum efficiency as well as consistency of terminology. Use solutions that are designed and configured to work together; otherwise you’ll spend time and money trying to connect the dots instead of analyzing the information. This shouldn’t be limited to digital information, but should include CRM, calls, web analytics, testing, advertising, etc.

3. Invest in Time & People

Spend the time to do the research on big data solutions, recommendations from the field, retailers, etc. Big Data is still young, so this will be a continuous process and the technology will evolve. You’ll need to educate people to evolve with the technology and methodology in order to analyze different types of data sources and integrate new technology. A statistician and developer will most likely be your number 1 priorities. The statistician is the numbers guru that will make sense of things, and the developer will help connect the information to solutions with APIs.

4. Consistency of Language & Terminology (classification) across the company

Everyone across the organization must use the same language regardless of their geographic location, and the definitions must be documented. You should think beyond metrics and include meta usage as well as tagging. If not, you’ll run into issues integrating the data and people understanding what reports or dashboards are showing.

5. Leverage Statistics

Leverage your statistician’s experience and expertise with testing that drives business success. In college, most of the business programs required statistics, and it’s time that you start using it!

Here are a few ideas that I would recommend:

Correlations can show you whether and how strongly pairs of variables are related.
Probability can be used to measure and predict when an expected event is likely to occur in the future (conversion).
ANOVA tests can be used to determine impact the changing a single or two factors has on a measured outcome (a headline has on the CTR).
Regressions analysis can be used when the focus is on the relationship between a dependent variable and one or more independent variables (marketing surveys)

Part 2 of the Top 10 Tips to Move Toward Big Data & Enterprise Solution will be available next Wednesday, September 19. For the most part, this first half focused on your organization internally. The next 5 tips will focus more on demonstrating the value. Stay tuned for the next part!

Successful Campaign Analysis Via Tagging Strategies

August 29, 2012 by Dabrian Marketing Group Leave a Comment

There can be a lot of unknowns when it comes to marketing campaigns. Who’s seeing your ads or print pieces? Of those people, who are they resonating with? Are your strategies working? These are all very important questions, that if answered, can lead to valuable insights into improving these strategies. But how can you gain visibility into these in the first place? If these marketing initiatives are designed to drive traffic to your company’s website, you’re already headed in the right direction!

If you have advertisements on billboards, print, you likely already have a web analytics platform selected to measure your site. If not, what are you waiting for? If you are using a platform like Google Analytics, you can mark your campaigns for easy analysis via URL tagging. New to manual tagging? Here are a basic outline so you can get the most analysis out of your campaign data.

Identify Advertising Methods & Locations: The first step is to get your ducks in a row by laying out all of our advertising methods. What type of ads will they be? Where will they be placed? What will the call-to-action be? What URL will be featured on the ad? These are all things that should be considered before proceeding.
Evaluate Campaign Flexibility & Constraints: It is a good idea to identify any strengths and weaknesses with the campaign. Are the placements permanent, or is there flexibility to change the ad up periodically? It is good to know whether or not you will need to prepare additional tags for the different ad variations, be it a billboard or a banner ad.
Create Information-Rich Tags: Now that you have all of the information you need, it’s time to make sure you carry as much of it over to Google Analytics as possible through information-rich URL tags. What do I mean by this? For Google Analytics URL tagging, you have the option of using several different fields for labeling, including campaign source, medium, and campaign. There are also other fields like term and content which will allow you to differentiate even more. You’ll want to make sure you get as much information as you’ll need down the line. The more information there is, the deeper you can drill down for analysis in the future.
Test, Test, Test! This step is pretty self-explanatory, but perhaps one of the most important steps of all. You should the new tags with their URLs to ensure that they send you to the proper page, as well as verify proper data collection within Google Analytics. You don’t want to find out after deployment of these tagged links that something isn’t right!
Deploy & Analyze: And now, the waiting game! Once enough data has begun populating in your analytics profile, you can begin slicing and dicing for deep analysis!

It is important to understand that this entire process can be time-consuming to start, but will serve to be a wise investment as the data comes rolling in. The insights that will be brought forth will be well worth it, as they’ll help you understand how well all of your advertising is performing, regardless of the medium.

3 Roadblocks in Web Analytics and Ways Around Them

August 1, 2012 by Dabrian Marketing Group Leave a Comment

If you’re reading this blog, you probably already understand that a great deal of marketing power can come from web analytics. If you’re an analyst, then we share the same pride in being able to take those high level metrics from tools like Google Analytics and slice and dice them to reveal tasty morsels we call insights. We’ve got a wide variety of tricks up our sleeves to help us accomplish this; from cohort analysis to predictive models. But none of that means anything unless you can get the buy-in needed for measurement to even take place.

I’ve written past blogs about getting the support from the decision-makers on data. This included creating a data-driven culture and developing KPIs that matter to form a solid measurement base. These are great, but only once you’ve gained the ears of the prospects. What do you do when they start spatting out excuses?

Excuses, Excuses

We’ve all heard them. In fact, we could all probably write a book with all of the excuses we’ve heard on why web analytics just aren’t a part of an organization’s immediate future ranging from budgetary to resource woes. Here are 3 excuses I’ve come across in the past and ways to help the prospect overcome them:

“We know how many hits our site gets.” – Okay, so the first one on the list isn’t an excuse….directly. This statement is enough to make any web analyst cringe, though. “Hits” don’t even scratch the surface of what web analytics can measure.Solution: Flex those analyst muscles! Explain to them that web analytics goes well beyond measuring “hits”. Wow them. Tease them. Tie it back to dollar amounts by showing them some examples of ROI analysis. With some persuasion, you can quickly open their eyes to a much larger analytical world than they originally thought they saw.
“We’re focused on marketing initiative XYZ right now. We don’t have the time.” – This one’s pretty common to hear, especially for agencies looking for new prospects. Unbeknownst to them, however, holding off on developing measurement strategies could severely impact marketing initiative XYZ.Solution: To overcome this kind of scenario, your best bet is to get more information on the initiative they’re so focused on. Once you have a better understanding of what they’re currently pursuing from a marketing perspective, you can show them how a measurement plan can help save them time and money as well as create efficiencies. We quote the movie Jerry Maguire here in the office a lot. This seems like a good time to do it: “Help us help YOU!”
“We don’t have the right talent or skill-sets in-house.” – This is a sad truth that exists in today’s business world, though it is starting to dissipate. Avinash Kaushik has astutely pointed out in the past that web analytics is in its awkward teenage years. Tools are improving and new strategies are being developed for their uses. Progress in these areas has been completely largely by companies and individuals. It hasn’t been until recently that the industry has started to gain the attention of some educational institutions.Solution: If you’re an agency, hand them your consulting information! If you’re not, find an agency! There are countless web analytics agencies out there that will do everything from full blown implementation and analysis to high-level consulting and guidance for your organization. Good insights only come from organizations with data-driven cultures. This has to start somewhere, so make sure it starts the right way!

Keep in mind that these aren’t likely end-all solutions to get the right kind of buy-in for web analytics. One thing is certain though: The greatest way to gain widespread support for the discipline is to continue spreading the word! The importance of measurement is already (albeit slowly) gaining traction in the business world.

Have you come across some other interesting roadblocks? Share them in the comments below!

5 Tips For Making Your Data a Top Priority

June 27, 2012 by Dabrian Marketing Group Leave a Comment

Whether you’re a marketing manager for a private organization or a web analyst for a digital agency, you surely understand the great importance of data and the powerful insights it can yield. You’ve also probably encountered one (often frustrating) roadblock: The people around you just don’t get it. The business analysts haven’t gotten the historical data you requested. IT has adopted a “we’ll get to it when we get to it” approach to installing tags on the website. Upper management doesn’t share the enthusiasm that your department does.

These factors almost always lead to marketing inefficiencies for the long term, with your organization’s proverbial marketing rear-ends hanging in the wind. Without quality insights, marketing campaigns cannot improve and are ultimately doomed to fail.

Tips for Success

So how do you go about creating a data-driven culture in your organization? Check out these tips to help convey the importance of data and insights:

Get Everybody On Board! – This is perhaps the most important item in this list! Measurement simply cannot happen without the complete support of the required parties in the organization. Make sure everyone, from IT to the decision-makers, knows what you are measuring, why you are measuring it, and how it affects them.
Establish Data-Gathering Policies & Procedures – You’ll be measuring with the goal of gathering insights to drive business, so you will want to ensure that the data you’re basing it all upon is of good quality. Establishing policies and procedures related to data and documenting them will take some time, but it will definitely pay off in the long run.
Identify KPIs Relevant to Your Audience – At this point you’ve caught the eyes of the necessary people in your organization. This is where you reel them in completely. Identify the Key Performance Indicators that matter most to each of them. This will differ according to their respective roles. You want to ensure they see the benefits of their work!
Create a Measurement Plan – Once you’ve identified all of the necessary KPIs, you must map out how you’ll go about obtaining the data. Identifying opportunities for measurement and creating documentation for deployment are included in this step.
Get Hyped! – You’ve put all this effort into winning the right people over. Now it’s time to get excited about it! Show them why they should be excited about the insights they’ll be receiving. The more anticipation you build, the more likely you’ll have advocates for the long haul.

Conclusion

So there you have it; 5 great tips for creating a data-driven culture. Some of them will be easier to accomplish than others, but all are possible with enough planning and communication with the right people. The benefits that can be reaped from them greatly outweigh the challenges. The insights that can be gained from complete buy-in and support can help drive business and improve campaigns well into the future.

Have additional tips? Share them in the comments!

1. Experiment Integration within Google Analytics

Content Experiment’s integration within Google Analytics is much improved compared to Web Site Optimizer. Web Site Optimizer did not integrate with Google Analytics, which limited a user’s ability to obtain additional information about the test variations for each experiment such as time on site, bounce rate, or the possibility of segmentation.

2. Simplified Workflow with the Set-up Wizard

The simplistic workflow to implement an experiment is streamlined as well. The process went from 5 basic steps to 4 basic steps. The set-up wizard for the experiment clearly identifies where you are within the set-up process and the next steps. In addition, there are icons to help you throughout the process to understand what you’re doing.

3. Visuals of the Experiments within the Console

The simple workflow is enhanced with visuals of the experiment variations, which was not part of Web Site Optimizer. Within the console of Google Analytics Content Experiments, you can see exactly what your original design vs. the variation(s) will look like prior to launching the experiments.

4. Better, More Simplified Reporting

In my opinion, the reporting in Content Experiments is much better than before. Content Experiments provides high-level experiment detail at a glance (visits, days of data, status of the experiment, and percentage of included visitors). The conversion data is also much improved by providing separate columns for visits, conversions, conversion rates, and basic green & red arrows to compare the variation(s) to the original page. Finally, the look of the reports is now more consistent with the newer Google Analytics interface.

5. Rewrite the Variation URLs to the Original within GA Content Reports

By selecting to rewrite the URL variations, you can consolidate all of the traffic to your original and variation pages. These URLs will appear under the original page within your Content Reports. This ability makes the Content Reports easier to read and streamlines the analysis of the experiment’s impact on page metrics in addition to its data. This provides increased functionality with custom reporting and experiment segmentation.

What’s the BIG Deal with Content Experiments?

The simplified shift from Web Optimizer to Content Experiments will save companies and marketers’ time, money, and allow them to easily create testing experiments. Ideally, Content Experiments will reduce the amount of time to create experiments and simplify their data, making them easier to understand as well as more actionable. With more actionable information, companies and marketers should be able to improve their users’ online experience and generate higher conversions.

Get off the excuse bandwagon! Start experimenting for better lead generation and online sales, what are you waiting for? Leave your feedback on Content Experiments in the Comments section below!