Is Big Data Relevant in Digital Analytics? Small Data first, then worry about Big Data

Big Data is a term that stirs a lot of excitement in digital marketing.

And a lot of anxiety for CMOs, Heads of Analytics and Digital/Web Analysts who wonder, Is my company getting the most out of Big Data?

These days, Big Data is a big deal. According to ABI Research, global spending on Big Data will grow at a compound annual growth rate of 29.6% over the next five years, reaching $114 billion in 2018.1

In addition, Science Daily estimates that up to 90% of the world’s data has been created in just the last two years.2 That’s part of the reason why the amount of data in the world is roughly doubling every couple of years.3

There is a lot of data. No doubt.

And there is a lot of money at stake.

What’s Big Data worth if I cannot get value from it?

Getting value from data is a challenge that transcends industry (finance, e-commerce, media, FMCG, travel, etc.) and company size (startup, medium-sized, large, global corporation).

In its initial phases, however, this challenge is largely independent of the amount of data available. If the processes and organisational structure designed to get value out of data are not in place, then it does not matter whether companies have lots of data or, at least by today’s standards, relatively little data.

So it’s worth asking: Is Big Data relevant to my organization? Now?

With Big Data, sure, you can find what you need. But if you do not know what you are looking for, then having more data just makes it more difficult, more time-consuming and more resource-intensive to get any value out of the data. For example, with lots of data, it can be hard to find what you need, your KPIs

KPIs can get lost in Big Data

KPIs can get lost in Big Data

 

 

 

 

 

 

 

 

 

 

If you start with Small Data, it is easier to find the data that drives value to your business:

KPIs are easier to find in Small Data

KPIs are easier to find in Small Data

If you already know your true KPIs and get value out of loads of data, then congratulations!

Many businesses are just not that far…yet.

Walk, then run: Focus on the data you need, not on the data that is available

In general, there is a three-step process to approaching the question, Is Big Data relevant for my organisation?

  1. Determine what data is needed
  2. Get value out of the “Small Data” at hand
  3. Move on to more value from more data

The key to getting value out of your data is determining what data you need. This is driven by your business goals. What factors influence the success of your business? What drives revenue and cost savings? Knowing these answers will determine which data you need.

Digital Analytics Business Value Framework

Digital Analytics Business Value Framework

 

 

 

 

 

 

 

 

 

 

 

If you do not know what data you need, then it does not matter how much data you have.

Once a digital analytics team knows what it needs and what it is looking for, then it can focus on conquering and getting value out of Small Data. Only after an organisation derives value from Small Data is it ready to tackle Big Data.

Is your organisation ready for Big Data today?

Many companies today should focus first on getting value out of Small Data before spending money and resources to get value out of Big Data. Take a look at this graphic and ask to yourself, honestly, where your organisation is in terms of getting value out of your data:

 

Data driven business value

Data driven business value

 

Many organisations are in the Reporting phase. Some have moved on to Analysis. Fewer have reached Insights. For those organisations that just spit out reports on website performance, Big Data is likely irrelevant for analytics efforts.

Factors enabling a company to get value out of Big Data

There are various indications of being ready to move up the scale from Small Data to Big Data, some of which are:

  • Dedicated analytics resources/team
  • Clear and powerful KPI structure
  • All teams in the value chain sit together
  • Head management directly involved with the data

Dedicated analytics resources/team

A key to success with data is having a team 100% dedicated to analytics. An analytics team, for example, that consists of a single person responsible for search and analytics and social media is an indication that worrying about Big Data may be a waste of resources. Analytics is a lot of work. People working on analytics should be focused on it and responsible for it.

Clear and powerful KPI structure

Once your organisation, driven by an empowered and capable analytics team, has a strong set of KPIs in place, and is proving that it can deliver business value on the existing data at hand, then that team may be ready to move on to bigger and more data sets by applying those processes and best practices to Big Data. Some examples of false KPIs are usually Visits, Visitors, Page Impressions, Engagement, Loyalty, Bounce Rate or Conversion Rate. KPIs are revenue, costs and the direct metrics and factors that lead to increasing revenues and decreasing costs.

All teams in the value chain sit together

This factor is often underestimated and it is related to silos. Many parts of an organisation are required to get value from data, whether it be Small Data or Big Data. The IT team needs to capture and store data. The analytics team needs to analyse and provide insights and recommendations on data. The content team needs to make proposed changes to the website or app. The marketing teams need to analyse data and create marketing content and optimise spending. Search teams. CRM teams. And more. All of these teams are (or at least should be) working towards the same business goals.

The closer those groups sit together, the higher the chances of getting better results. The best case is when these teams sit in the same room. At least in the same floor of a building. While it may seem utopian for some organisations, it does increase the chances of getting value from your data. And there are organisations that are moving in this direction.

Head management in the data

The shorter the distance between the person in charge of the data and the leading management of a company, the likelier it is that a company will be successful with data. This might mean having a Chief Officer – a Chief Marketing Officer, Chief Digital Officer or Chief Data Officer – who works directly with data. It could mean having a Head of Analytics. It could even mean having a great Web Analyst who has the ear of top management. When the highest-ranking person in analytics is low on the organisational chart (either officially or unofficially), then the role and importance of the data in the organisation will follow.


While every company is different, some basics are similar

These four points are just factors to success from various customers (large and small organisations) from various industries (e-commerce, travel, finance, media and more). Each organisation will have its own unique constellation. And dealing with lots of data (Big Data) is almost unavoidable today. But with the organisational basics in place, as indicated in the above four points for success, your organisation has a good basis with which to dig into the data itself, which is hard enough as it is.

Without those basics in place, getting value out of your data will be even harder.

Spencer Altman


Previous Post Next Post

You Might Also Like

No Comments

Leave a Reply