Why a data-first approach is no longer optional in the marketing mix

The digital revolution is over and its victory is complete. There is no way to avoid the fact that every marketing decision needs to revolve around data – and marketers shouldn't try to avoid this. Exploring a data-first mindset it vital to achieving marketing success.

I chatted with Richard Whale, head of marketing, international at Avention OneSource Solutions, to explore the tools and technologies for making the most out of data and how the change in mindset to being data-first can deliver real results.

Why should B2B marketers be adopting a data-first approach to their work?

Data’s role in marketing has really evolved in recent years. For many B2B marketers, data used to be an afterthought: we would produce and design programmes before actually looking at the data needed to execute them. Today’s landscape is very different, with technology now an essential part of marketing, and this technology lives and dies on that quality and breadth of the data that underpins it.

Take account-based marketing (ABM) as an example. The benefits of ABM are widely acknowledged in the industry, but the focus has predominantly been on the ‘shiny new technologies’ used in the execution phases. However, one simply can’t put an effective ABM strategy into place without access to the right data. Without the right internal and external data, you won’t have the business insights that you need to understand the market, accurately identify accounts, and target the right contacts before initiating your programmes across the many tech platforms now available.

How can B2B marketers use data to make a demonstrable impact?

I’ll put reporting data and measurement to one side at this stage. Earlier in the process and then throughout programme management, data gives B2B marketers the insight into industries, companies and contacts they need in order to fully understand their target markets. This, in turn, enables them to be far more targeted when identifying potential customers to approach. OneSource DataVision, for example, increases the value of existing customer and prospect data and information by bringing together multiple data sources – both internal and external – and then analysing and visualising them within a single view. This means marketers can understand their current customer bases in detail and identify the most relevant target companies and segments to engage. These tools and the access to insight they provide can put power back in the hands of marketers to shape their business’ strategy.

Lots of marketers still don't use marketing automation (MA): why do you think this is?

MA isn’t a panacea, and certainly isn’t right for 100 per cent of marketers. In fact, it’s a big mistake for a business to assume that MA will solve all of its problems, since without clear objectives and sensible implementation, it will cause more work and headaches. MA technology is by no means an end in itself, and marketers still need a deep understanding of their audience to deliver relevant, compelling and valuable content (and for this, you need the actionable insight that comes from good data). Lots of businesses have also made the mistake of rolling out MA tech that is overly complicated. This is just asking for trouble, since many of these companies don’t have the data and insight to support this complexity, not to mention the resources to deliver a constant stream of relevant content.

Who are the people you need in your team to be able to implement MA properly?

It’s not just about who you have in your marketing team, but across the whole organisation. Depending on what your setup is, IT will have a major role to play and it’s imperative that the team is on the same journey as sales and marketing. Both departments need to have a common understanding of what success is and what good looks like, or the implementation simply won’t work.

What are the challenges of marketing automation?

MA providers do a great job of selling their solutions as ‘plug-and-play’, but I challenge you to find anyone who has actually found this to be the case in practice. Introducing MA is a transformational programme that impacts far more areas of a business than just marketing – sales, IT and operations. Therefore, it needs to be built on a really solid foundation of data across the entire business, and having accurate, regularly refreshed information – like name, address, industry etc – is essential. You also have to remember that, when executed properly, MA is about managing on-going engagement to provide relevant content at the right time. For that you’ll need additional insight into your contacts – both from the behavioural data you’re collecting via MA and other platforms and from external information.

What other data technologies are vital to a marketer's arsenal? Any why?

The martech space has expanded exponentially over the last few years but the area is still deeply confusing for most. Ultimately, which technologies are considered vital depends on the business, the audience and the strategy. My advice is to keep it simple and employ the fewest number of platforms as possible, otherwise you’ll risk burn time and effort managing them all and be spending time on internal processes rather than engaging your customers. Those that you do use must be integrated wherever possible – this will help eliminate multiple, disconnected views of how your customers are engaging across channels and touchpoints.

How long can those reticent to adopt a data-driven approach continue before they're left behind?

They have already been left behind. Every marketer today needs to appreciate how a data-driven understanding of their customers and prospects will better focus and direct their efforts. A data-driven approach to marketing isn’t something that should be restricted to the CRM team, data analysts or digital marketers, for example: it has a role to play in every single function and can actually be the connector between those functions. It’s really good to see that more marketing courses are placing data front and centre, and I would advise those marketers who are further along in their careers to actively look at what gaps they have in their knowledge and skillset and take action to fill them.

What should marketers struggling with reticent colleagues be doing?

For those without a data mindset, this shift can be quite daunting – not least because the majority of organisations don’t have the right data infrastructure (disparate systems, inaccurate or out-of-date data etc), which only compounds people’s discomfort about their lack of skills in the area. It’s often seen as being too big and too hard to deal with, which leads to data paralysis. People need to remember that their data capability doesn’t need to be – and almost certainly won’t be – perfect straightaway, so it’s important to set small milestones as part of the transformation. Doing something to point your business in the right direction is far more positive than doing nothing at all.

What does success look like?

Marketing success should not be measured by the volume of activity, or even by MQLs. This is a common trap that one call fall into when marketing automation plays a pivotal role in marketing strategy – high volumes of activity but losing sight of the real impact to the business. Whether heavily technology-reliant or not, success still boils down to two simple but hard-to-achieve outcomes: driving incremental revenue for your business, and delivering relevant, valuable experiences to your customers and prospects.