CMOs: 3 Keys to Extracting Value From “Big Data”

If you’ve got analytics, you have insights waiting to be discovered. Are you finding them and using them to drive value for your business?

There are few things as full of hype, promise and sexiness as “big data” and we have more data than ever before, yet marketers are challenged to parse terabytes of noise to get a megabyte of signal.  Too many practitioners are focusing on reports and dashboards instead of analysis, and not reaping the promised benefits.

I am a student of the art and science of digital marketing, which is increasingly driven by the principles of decision science and continuous improvement that have informed my career in large-scale content production management. I am currently studying Social Media Marketing through Northwestern University. The purpose of this blog is to both practice the craft and share the best bits of what I’m learning along the way. Today’s catch includes 3 tips from two of the industry’s top minds on how to get the biggest bang for you big-data buck.

#1) Use the Scientific Method

Andy Crestodina at Orbit Media Studios challenges would-be big data mavens to do more than monitor reports and truly embrace the analytical process by doing the following:

  • Get a marketing idea
  • Ask a question that supports the idea
  • Find the report that provides the answer
  • Proceed with the idea (or reject it) based on the answer
  • Measure the impact

In short, Andy suggests following the scientific method which includes forming a hypothesis, challenging it with data, and using the resulting insights to make better decisions and do better marketing.

Andy Crestodina

“There is an ocean of data in your Analytics. And it’s fun to swim in the ocean. But it doesn’t really get you anywhere. If you’re just looking at reports, without answering questions, testing hypotheses or drawing conclusions, you’re not doing Analysis.”

– Andy Crestodina

 

He then goes on to give an easy to follow example of this process for each of the four reporting categories found within Google Analytics; Audience, Acquisition, Behavior, Conversions.

For example, do you think increasing social media activity might generate leads? Ask the question, “Which social network refers the most engaged visitors to our site?” A Google Analytics Acquisition report can tell you where referrals are coming from, what pages they are visiting, and how long they stay, and whether conversion rates vary meaningfully from other sources. The answers can determine whether it makes sense to test the idea. If so, measure the impact and see if the original hypothesis is proven correct. Either way, you can repeat the process to further refine the strategy’s performance or explore other options, compiling valuable insights on what does and doesn’t work along the way.

Read the full article “Google Analytics Reporting vs. Analysis: Insights From 4 Reports

Big Data Mountain

Anyone entering the realm of digital marketing and analytics will soon recognize Avinash Kaushik as a key thought leader in the industry. On his blog, Occam’s Razor, Kaushik has written extensively on how to use big data to find insights that drive action with timely value.

In his blog post, “A Big Data Imperative: Driving Big Action“, Kaushik acknowledges the potential and the challenges posed by big data.

Avanish Kaushik

“It is great that we have big data. It is greater that we have such amazing promise in that big data. It is sucky that almost no one knows what to do with it in the context of driving actual business value.”

– Avanish Kaushik

 

 

#2) Invest in people, not tools (the 90/10 rule)

Kaushik is adamant that for every $100 budgeted to invest in making smart decisions, invest $10 in tools, and invest $90 in big brains (aka people).

Don’t build the biggest, baddest big data environment over 32 months, only to realize it was your biggest, baddest mistake.”

Computers and artificial intelligence are simply not there yet. Hence your BFF is natural intelligence.

Let the 10/90 rule be an inspiration to simply over-invest (way over-invest) in people, because without that investment big data will absolutely, positively, be a big disappointment for your company.

While systems and tools can provide access to massive quantities of data, with ranks of impressive reports and dashboards, actionable insights that drive value remain the province of the analyst. Be sure to invest your budget accordingly.

#3) The Digital Marketing and Measurement Model

To aid “big data revolutionaries” in their quest, Kaushik has published a five-step framework called “The Digital Marketing and Measurement Model”, which contributes to structured thinking about what the real purpose of a campaign is, and the determination of an objective set of measures with which to identify success.

  1. Identify the business objectives upfront and set the broadest parameters for the work we are doing. Sr. Executives play a key role in this step.
  2. Identify crisp goals for each business objective. Executives lead the discussion, you’ll play a contributing role.
  3. Write down the key performance indicators. You’ll lead the work in this step, in partnership with a “data person” if you have one.
  4. Set the parameters for success upfront by identifying targets for each KPI. Organization leaders play a key role here, with input from Marketing and Finance.
  5. Identify the segments of people / behavior / outcomes that we’ll analyze to understand why we succeed or failed.

Follow this link to read the full text of Avanish Kaushik’s post on “The Digital Marketing and Measurement Model

Remember these 3 keys to driving value from big data

  • Be Scientific: Start with an idea, convert it into a question, find a report that answers it, reject or proceed with the idea, and measure the impact.
  • Invest in People: Direct 90% of your analytics investment in people, who are your source for actionable insights.
  • Follow the Model: Define the objective, set goals, document KPIs, determine success parameters, identify causes for success or failure.

Follow these three principles and make the difference between good and great marketing.


 

Nick Krueger is a 17-Nick Kruegeryear veteran of the analog magazine publishing and retail marketing communications business, with the last 9 years managing the execution of print marketing programs at RadioShack. 

Nick has a B.S. in Operations Management from the University of Memphis, an M.B.A. from the University of North Texas, and is currently enrolled in Social Media Marketing with Northwestern University via Coursera

You can find Nick at LinkedIn, Twitter, Google+, and Facebook.

How Big Data Can Help Your Business Thrive

Big Data Matters

If you truly want to make an impact on your company’s bottom line, you need to know what type of people are interested in it. Being privy to this information will allow you to preempt their needs and meet them head-on through strategic targeting.

One example of this exists in the gaming industry, where effectively marketing their product towards those customers who would be most interested in their product. An unfocused marketing campaign that targets a very general audience would be ineffective, and can cost a company thousands in lost marketing dollars.

So where do they get this information? Information aggregation services employ analytics experts, or data scientists, who interpret customer behavior from reams of raw data. With this information, changes can be made with the aim of maximizing revenue. In one case, a game manufacturer was able to double its revenue to over $100 million dollars through simple tweaks to game design that targeted common customer characteristics.

The important thing is to pay attention to your customers and make the appropriate changes, and that’s what makes “big data” so exciting: it can be extremely lucrative, regardless of your specific business niche.

The Growth of Big Data

With the explosive growth of social media and the Internet in general, marketers began to realize the power of harnessing both to increase brand awareness. Later, they discovered that they could learn a lot about their customers’ spending habits and interests by monitoring their online activities.

However, with over 9,000 tweets sent per second, it can seem impractical to dedicate time to understanding and interpreting customer behavior through such a vast amount of data. Even Google had attempted the enormous feat of indexing tweets back in 2011, but ultimately failed.

Even worse, some financial officers may be cross to budget for social media departments due to the department’s inability to provide a tangible ROI. In fact, many social media departments are shut down entirely due to not having set goals. If the department can’t prove that it’s making a difference in returns, it doesn’t have a chance of survival.

And that, sadly, is where many companies get it wrong. You can’t simply jump on the social media bandwagon and specifically assign a team to do just that. Rather, an integrated approach that utilizes all facets of big data would effectively cover all of your bases and provide you the valuable insight to make informed decisions.

Psychographics Fill in the Gaps

Where demographics cover the basic physical traits of a customer base, psychographics go one step further by observing customer behavior. In essence, it takes into consideration the customer’s social identity and modifying marketing efforts to meet that identity. Where demographics can be lifted from readily available tools, psychographics are not.

The basic goals of psychographics are to retrieve customer insight by:

  • Getting to know them
  • Observing their behavior.
  • Asking questions.

As the previously mentioned game manufacturer clearly displayed, customer behaviors were observed, studied and met with relevant changes to game design that netted double their normal revenue.

Even better, the natural steps that come from studying psychographics also generate brand loyalty. When a company takes proactive steps towards connecting with their customer, the latter will feel more valued and will likely recommend the business to their friends and family.

Word-of-mouth recommendations are also very powerful at creating brand awareness and helps companies avoid the old school and inefficient method of “cold calling” potential customers.

Examining and acting upon what motivates your customers will generate more accurate leads than simply pandering to what’s shown in a demographics spreadsheet. Just because your customers share the same age group or income level doesn’t mean that they have the same interests.

Instead, find out what motivates them and where they interact most.

Examples of Big Data in Action

Where using big data can help a company effectively connect with their customers, it can also be used in other areas, such as company expansion. For example, Wendy’s recently utilized a GIS service called Esri to help them determine where to build new stores. When ran, the system gives planners demographic information on nearby residents and sales records, mostly pulled from public records.

After the economic downturn of the economy in 2008, many companies have turned to services like Esri to reduce the risk that comes with a serious investment like expansion. However, it has also been used in more customer-centric approaches as well, like with Ascena Retail Group, Inc., which owns brands Maurice’s, Dress Barn & Justice. All three of these brands cater to three distinct audiences, and through the use of big data, Ascena Retail was able to stratify all three brands and effectively plan for their integration based on socioeconomic information.

Regardless of your application, big data can help you significantly reduce your risk and help you make informed decisions in regards to marketing and planning. The chances of a return are much greater if you make a genuine connection with your customers, and part of that is fulfilling a need before any of them knew they had one.

This excerpt is from the Innovation Excellence. To view the whole article click here.