Five reasons why data is the most valuable asset a company owns
Data seems to be everywhere in the news right now, from the Facebook data breach of 87 million users earlier this year, to the new General Data Protection Regulations (which you can read more about here), but why all the fuss? Why are we seeing more regulations and breaches surrounding data?
Data is one of the most important assets for any company and its correct (or incorrect) management will have a huge impact on success. Our top five reasons why data is such a valuable asset are:
- Website data can help you better understand your audience types and behaviours.
Even the most basic website is likely to be collecting data on its users through Google Analytics or other analytical platforms. Data collected will typically include:
- Audience types, such as your demographics (age grouping and gender), device types, geographical locations, other interests (based on other sites visited) and more.
- Acquisition channels – letting the website know where the user came from (i.e. a PPC campaign, social media, direct, email, etc)
- Behaviours – how the users are interacting with/flowing around the website
- Conversions – such as website goals (i.e. newsletter sign-ups) and eCommerce reporting
Before you panic, nothing collected on Google Analytics is considered personal data (i.e. you cannot identify an individual through Google Analytics), but it does provide marketeers with insightful information to make decisions on their campaigns.
For example, let’s say an eCommerce website is selling t-shirts online. Analytics can be used to see the demographics of the users who view (and buy) the product. Understanding the various demographic eCommerce conversion rates can then help the store better target the users who are most likely buy the t-shirt in future campaigns, potentially saving costs by limiting wastage and returning a more effective CPA.
Some may take this a step further with user-based tracking. Again, don’t panic - this can only happen if visitors have willingly surrendered their data (perhaps by filling out a form on a website). This is when a site has the capability to drop a cookie onto a machine. The cookie can then track interactions with the website and its campaigns, allowing marketeers to create very bespoke campaigns or sales teams to know what content has been read prior to that annoying sales call.
- Transactional data helps to quickly identify failing or succeeding product lines & trends
OK, so you may know your stock levels – but do you really know how successful the product is? And is the product gaining traction with your intended audience? Or perhaps you are seeing an unexpected dip in sales. Careful analysis of your data can again help to answer these questions.
Let’s take the t-shirt sale example again. Analysis of traffic levels to the page versus sales tells you just how popular the product is (or the eCommerce conversion rate). This understanding is vital for companies to quickly understand what products are performing as expected, or which products are failing to return expected sales.
Struggling products can then be put into an A/B testing programme to help refine the product until it sells at expected conversion levels. However, it’s not just the low-level products that should be identified; products selling at a strong conversion rate should also be analysed as the price-point may be too cheap, or other factors may be causing the uplift, which could be replicated across other lines!
Finally, your data can also help you understand and manage trends, for example looking into your product lines to understand when seasonal buying habits begin.
- Enhanced experiences to uplift sales
Have you ever wondered how Spotify, Netflix, Amazon and so on recommend items that are aligned with your likes? Well, services and sites like these use machine-readable data (also known as structured data). This is data/information that computer programmes can process. On Amazon, this data helps encourage navigation around the website and will retarget users through email with the aim of upselling products. When coupled together with personalisation, this data-driven persuasion tactic can be very effective at generating additional revenue.
- Relevant data creates strong strategy
Incorporating data ito your strategy allows you to answer the most important question…. why? Why has this approach been taken? Why that channel? Why that audience targeting and why that timing?
Let’s look at a typical hypothesis: ‘Because of X, I believe Y, which should result in Z.’
Only relevant data can give you the X in the hypothesis, and only data can give a steer to the resulting Z (typically a KPI) – otherwise the hypothesis can only be based on opinions (and experience).
While opinions (and experience) can lead to some fantastic results, having a hypothesis based on relevant data, enables you to be proactive and achieve more goals, while limiting problems/issues that you wish you had caught sooner.
In short, data will allow you to produce a stronger, more informed strategy and adhere to one of the fundamentals of business, the 6 Ps (Proper Planning Prevents Piss Poor Performance).
- It can identify opportunities
Strong data analysis may help identify unexploited areas of your business. For example, your online e-commerce business could expand into bricks and mortar locations, but where? A deep dive into your data could reveal the locations most aligned with your products, helping to inform the decision-making process.
In summary, data (be it transactional, personal or metadata) is vital for businesses to target their audiences, influence decisions, limit wastage and enhance user journeys. Together with the evolution of technology, we are seeing some fascinating marketing techniques – such as advertising boards that scan the user to display more relevant ads. Creepy? Perhaps… but I’d rather see advertisements that are relevant to me, as long as data privacy is not breached and the chance to opt out is made available.
Thankfully, here in Europe, GDPR regulations are now in place and enforceable – meaning any company that has mishandled data or not followed the regulations could be liable for fines of up to €20 million or 4% of annual turnover (whichever is greatest). US law has not yet caught up, but in the wake of the recent Facebook hearings, change is likely.