Drowning in Data? A Practical Guide to making data work for your business

How can you make data work for your business?

Last Thursday as part of Leeds Digital Festival, iProspect Leeds invited a select group of people into 6 East Parade to hear from three of our agency’s strategic thought leaders; Scott Boyes, Jamie McGrath & Ian Williams on how to plan and execute an effective data strategy to drive value to your business.

With so many key topics to explore, after much debate we settled on data as it is one of the most over-used terms, yet seemingly least understood concepts in marketing, despite being such a critical component to driving business performance.

Big Data is like teenage sex…

Dan Ariely , Professor of Psychology & Behavioural Economics at Duke University said it best…

”Everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it too.”

The universal truth is that data is critical to the future of business, yet the number of businesses who truly have a grip on their data are few and far between.

There is much talk of data in our industry, big or otherwise, yet in many instances – that is all it remains – hot air blown by ill-informed professionals who don’t have the skills or the tools to get to the heart of the challenge. We’re prone to spending time navel gazing, looking at what data-driven business can deliver, rather than thinking about how we develop the infrastructure to make it a reality.

Despite years of hype we still see the same trends…

•  72% of businesses collect data they admit they will never use.
• 89% of FTSE 250, UK Public Sector & UK headquartered multinationals say they are not using big data to inform their decision making.
• Only 0.5% of all data created is ever analysed and used
• Every person in the world is forecast to produce 1.7MB of data every second of every day by 2020.

Marketers continue to resort to the lowest common denominator just to tick the box. Poorly executed dynamic retargeting strategies chasing one-time site visitors around the internet for months displaying pictures of things they’ve since bought from a competitor. Ill-conceived personalised emails displaying constantly revolving irrelevant products sent on a daily basis or hastily assembled contextual targeting campaigns based on huge sweeping assumptions.

Advertising is losing its relevance…

If you’re in the advertising profession, I’ve got some news for you, and you might not like it... You don’t have the power you think you do to determine people’s choices!!!

As a result of poor execution, advertising is becoming less and less relevant and the signs are there if we look at the right data!

Increasing numbers of people just don’t want to see our advertising any more as ad blocker penetration in the UK hits 22%. The IPA Effectiveness databank analysis by Peter Field also demonstrates a sharp decline in the business performance driven by advertising campaigns since 2010, yet no doubt we can all point to the data set that tells us entirely the opposite of both of these conclusions.

We need to stop using Data like a drunk uses a lamp post

Instead of using data as a crutch in an attempt to keep ourselves upright, we need to determine what is right, what is wrong and what is just completely unnecessary. There is no doubting data's importance but there are some simple common sense rules we can apply to our data strategy in order to ensure it is delivering value to us:

1.      Just because you can measure it doesn’t mean you should: There is no shortage of metrics to point to and if you look hard enough you can find something to correlate to the trend you need to prove to assume causation; that doesn’t mean it affects your bottom line or that your business is succeeding

2.      Data does not equal insight: Data is a collection of raw information or events. In order to deliver insight that data needs to be organised into information, interpreted to deliver knowledge and understood to achieve wisdom (Steven Tuthill, - “The Data hierarchy”)

3.      More data does not equal better insights: As with anything; quality clearly outperforms quantity. There is no shortage of opportunities to collect data, but what value does it add? Decide early on which data adds value to your business objectives and focus on that

4.      Don’t start with your data strategy, start with your customer strategy: unless you know who your customers are and what they want, the rest is an irrelevance. Build your data to understand and add value to your customers, not the other way around

5.      Don’t try and run before you can walk: it’s inevitable that from time to time we are seduced by possibilities and chase instant gratification without taking all the necessary steps to get there. Understand where you are right now and move forward from there one step at a time and you will create both the flexibility and the capability to achieve great things in future.

Legacy businesses don’t know where to start…

As an agency we are in the privileged position to look under the bonnets of lots of businesses at the point we start working with them and therefore understand how effectively they are managing and activating their data. All too often we find that customer strategy, marketing strategy and data strategy are confused and all three terms are used to mean the same thing.

One of our most common observations in legacy businesses (for the purposes of this article: businesses conceived and built before the birth of the modern internet) is that either they systematically fail to place an appropriate level of importance on an effective data strategy or they grossly overestimate their capabilities to collect, analyse and activate data, often delegating this to under-skilled and under-supported teams, yet confidently still rely on the insights to make very important decisions.

Often marketing channels develop their own approach to data in silos. The advent of retargeting technology through the likes of paid search, display and social media; three channels often managed by different specialists, leads to differing approaches to data segmentation and activation that aren't consistent.

When it comes to reporting, different stakeholders utilise different sources and interpret them in different ways in order to demonstrate effectiveness and quite often blame activities in other marketing channels to explain perceived negative performance rather than understand the relationships between them all and often inevitably leading to a set of reports indicating revenues three times higher than your bank statement.

Data Driven marketing works

Looking at our own client base we regularly see conversion rate increases of 2-3 x in the first 2 years following investment in a robust data-driven strategy across the entire customer journey, yet despite this we routinely see clients failing to invest in establishing effective analytics data collection, understanding how customers are interacting with their brand through advertising, on websites or in-app and implementing iterative test and learn processes to drive constant performance improvements in favour of more traffic or more eyeballs.

On average we observe investment in data collection and analysis solutions to make up around 7% of the overall budget mix, yet those who are seeing the largest improvements in conversion rates aren’t necessarily investing significantly more. Those seeing those increases in conversion rate of 2-3 times the start point on average have only pushed that investment in data management to 10-15% of their overall mix.

The future will be Data Driven

As technology develops and more platforms become capable of plugging into each other to leverage client data to drive actionable marketing outcomes, an effective approach to data has never been more business critical. An effective data strategy will drive many of the aspirational marketing tactics, commonly discussed in digital circles right now.

1.      Single Customer View: The ability to track a customer’s interaction with your business across multiple brand touchpoints on and offline to better understand their behaviour and cater to their needs

2.      Personalised advertising creative: The creation of dynamic reactive creative executions that recognise customers and tailor messages to their preferences and the environment in which they are displayed

3.      Personalised website experiences: The ability to tailor content on a page to a particular individuals' preferred products and services to improve retention and grow sales

4.      Recognise customers when they walk into your real world retail-space: Utilising beacon technology and mobile devices to connect online and offline touchpoints and tailoring in-store experiences to individuals

5.      Augmented Reality: The ability to overlay personalised content onto real-world experiences to engage audiences with brands

All of this is possible right now, but most brands have not given themselves the head start they needed by investing in an effective data infrastructure to execute them effectively.

There has never been a more exciting time to get started with data

Access to powerful technology to capture, analyse and activate your data is at an all-time high and there is no better place to start than your web analytics solution. As the effectiveness of free analytics tools such as Google Analytics begins to diminish with increased sampling and reduced data collection; enterprise-level analytics solutions such as Analytics 360, Adobe and Qubit become neccesary.

Businesses are often hesitant to invest when there is a free alternative (have a look at how much of your data either isn't collected or is sampled in GA - just because it's free and it has great visualisations doesn't mean it's actually reflecting what's actually happening) yet are willing to invest huge sums of money in media based on the so-called insight provided. In some instances we've come across the business might have been better checking their horoscope to understand what was likely to happen.

Effective setup is critical and defining business objectives is the starting point to getting this right. Marketing is more than just advertising; factors such as product, price and location can all be factored into an effective data strategy to create actionable insights that can drive decision making (either human powered or real-time automated) that improve the offering you take to your customers and drive real business results.

"Utility" is the most underused word in analytics

There are three key questions every self-respecting analytics specialist should ask themselves when deciding whether to collect a particular type of data:

Too often data is collected just for the sake of it and will never offer any value to anyone. Regularly we meet businesses who have ended up with messy analytics profiles; set up by multiple stakeholders in entirely different ways with absolutely no consistency between any of them - leading to every single stakeholder in the business having an entirely different view of what is happening.

If you were wondering… The second most underutilised word in Analytics is “Discipline". All too often we race ahead, overcome with excitement at the possibilities and create a data architecture that is inconsistent, rigid in structure and no use to anyone else other than the person who created it.

Three rules for an effective analytics data architecture:

*If the creator is ‘Hit By A Bus’ can someone else seamlessly pick up where they left off?

Good Decisions can only be made from Good – Clean - Data

All good things have a solid foundation. As identified well above – don’t run before you can walk and start at the start! Build a data infrastructure that reflects your business objectives and your customers and plan before you roll your sleeves up and dive in:

1.      Define your measurement principles: Ensure all data collected is accurate, delivers new meaningful insight, has a direct link to an actionable outcome and is efficient; minimising hurdles created for others

2.      Map out your customer journeys: Determine the journeys you expect your customers to take, incorporating all touchpoints on and offline. This gives you a hypothesis to work from and allows you to track deviations

3.      Create a measurement plan: determine your business and marketing objectives and set clear KPIs that both reflect delivery against those objectives and that can be clearly and accurately measured. Map all subsidiary metrics that contribute towards that KPI so you are aware of the variables you have available to you to influence your actions

4.      Keep innovating: Constantly look for ways to build value on top of your foundations. Enrich data with additional first and third party data sets as they become available. Use data to personalise experiences for customers and find ways to collect new valuable data. Plug your data into your marketing channels to better identify and target new audiences and put measurement and data at the heart of your brand experience; constantly testing and learning to improve customer experience for greater business impact

If you’re interested in talking about data, feel free to drop me a line!