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Tips to Move Towards Big Data & Enterprise Solutions Part 2

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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.

3 Roadblocks in Web Analytics and Ways Around Them

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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:

  1. “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.

  2. “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!”

  3. “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!