Data. It sits at the heart of the marketing function. Without it, marketers would be blind.
The old era of marketing was often dictated by gut-feel and creativity, or so the legend goes. Marketers guessed what their customers wanted, and weren’t held accountable for measuring success. However, the age of push marketing is at an end, and brands failing to adopt a data-first approach will be left with their thumbs up by the wayside.
It’s a cliché we’re all familiar with, but the internet has revolutionised the way marketers work. Instead of basing their labour on conjecture, marketers now rely – and rightly so – on the dialogue between themselves and their customers. And what underpins every single one of those conversations? Data.
Where are we now?
For modern B2B marketing teams wanting to adopt a data-first approach, working seamlessly with sales has become a fundamental aspect of the business function. Marketing and sales need to work together, from a common data set that’s all in one place. This will break down any pesky silos, and facilitate true transparency.
We’ve all heard the ‘X per cent of a prospect’s journey is already completed before they get to sales’ stat. And while the authenticity of the proposed figure is dubitable, the takeaway is this: the predictive journey created by marketing data needs to continue all the way through to sales.
"B2B marketers essentially have two customers: one is the prospect, who needs constant nurturing, and the other is the sales team"
Shannon Duffy, Pardot, Salesforce
As Shannon Duffy, VP marketing, Pardot at Salesforce, explains: “If a customer embarks on a buyer journey, where they are treated in a personalised manner during the first leg, and are then asked about their needs and wants at the sales touchpoint, that’s a poor customer experience.”
In order to prevent this from occurring, marketing needs to connect sales with common data sets, providing them with the visibility that’s key to successful data-driven marketing. Marketing tech equips marketers with the ability to provide the best possible experience for their prospects and, in doing so, the best possible source of leads for their sales team.
Lead scoring
This wealth of data allows marketers to rank prospects against a scale that demonstrates the perceived value that each lead represents to the business.
However, what sets lead scoring apart from other data uses is its human element: the data provides the basic information, but the human element provides the score the data is equated against. Data needs this human element to truly realise its potential, and this has to be exercised through close alignment of marketing and sales.
Yet this is where a challenge emerges, as Duffy observes: “B2B marketers essentially have two customers: one is the prospect, who needs constant nurturing, and the other is the sales team. The only way to serve both of those groups is with good marketing tech.”
And this is why consistency and objectivity are absolutely vital during the lead scoring process, allowing both sales and marketing to determine what’s important in order to effectively nurture a lead. More importantly, it allows marketers to identify the perfect time to hand over a lead to sales for conversion.
To truly prosper from a successful lead scoring campaign, marketing and sales will also need to reconvene post-activity, collaborating again in order to cross-reference leads to ensure high-quality prospects aren’t getting hammered with messages from all angles.
And it’s not just a homogenous sales and marketing relationship that’s vital to successful data-driven marketing, as Richard Whale, head of marketing, international, Avention OneSource Solutions explains: “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.
“All departments need to have a common understanding of what success is and what good looks like, or the implementation simply won’t work.”
Go holistic with your measurement
Data and metrics underpin everything a marketer does. As Duffy shrewdly observes: “The good thing about digital marketing is you can track everything, and the bad thing about marketing is that you can track everything.”
To combat this overload, all data needs to be kept clean and stored in one place. Big data is perilous in every sense: it’s wonderfully diverse, but potentially unmanageable if not treated with care and respect.
Poor data leads to poor decisions. To achieve data sanitisation, duplicates need to be eliminated, incomplete data fields filled in and, above all, all data needs to be constantly refreshed.
Another real danger is accumulating data in silos, resulting in a loss of focus and a failure to take a holistic view of your prospect, which is a vital technique for B2B marketers seeking to gain a comprehensive understanding of their customers.
Duffy observes: “If someone posts on your website or on social media, it’s not giving you the full picture. You have to look at the data cohesively, and in one place.”
This holistic approach allows marketers to track how each aspect of their marketing is impacting buyer behaviour, and can act accordingly. While qualitative, first-party research helps to understand the ‘why’, research from an objective third-party can often be the welcome input a brand craves.
Looking into the future with predictive analytics
Going that step further with data is not just about using your own data well, it’s about predictive analytics – the cutting edge of data – and buying in third-party data to enhance your own knowledge.
By overlaying first-party data with external data gleaned from third parties, marketers can vastly improve their understanding of their customers. Perhaps more importantly, marketers will possess the ability to identify previously untapped customers by matching them with a company’s best customer profiles and targeting them accordingly, using the combined data to find out the best time to reach them, and through which channel. That way, marketers will be able to track open rates, click-throughs and, most importantly, where the drop-offs are.
The power of this data ensures marketers can fix the drop-off issue immediately, as Duffy explains: “The power of harnessing this data means marketers can respond right away: they can take action rather than merely observing.”
Put simply, the key to successful, data-driven marketing is determining the right metrics to track and, most importantly, how to respond. Marketers know they have to make data-driven decisions, but building spreadsheets and pivot tables can be time and labour intensive, and doesn’t yield immediate results.
Predictive tools collect customer journey data, analyse their actions and note the path they took before the all-important purchase. The more of this information that can be gathered, the easier it is to predict positive outcomes: marketers will be able to tailor campaigns, hyper-personalise emails and truly deliver the best content and actions at the optimum time.
2016 has to be the year B2B marketers finally take the plunge and turn predictive analytics from theory into practice, from something they’d like to have but are too afraid to try, into something that truly drives prospect and customer engagement.