Customer expectations have changed in recent years
They expect businesses to know who they are and what they need. Personalisation is key – general messaging will not stand out from the noise and any potential prospects will unlikely engage with this approach.
Customers are also better informed than they once were. They want authenticity and transparency from the businesses they choose to engage with. Today organisations are less likely to have personal contact with their customers, but a transparent approach can build trust. That said – it becomes increasingly important that any content is supportive of these elements; showing how businesses understand their customers’ needs and that they are approachable to deal with.
Customer data is also subject to the privacy regulations within GDPR. Any marketing must be appealing and relevant to the target audience if organisations want consent to use their data. This can be achieved but it may require a different approach; think predictive analytics and artificial intelligence (AI) to create customer profiles and personalised campaigns that achieve these outcomes.
Changes in the buying journey
The rise of content marketing has provided a raft of educational marketing material to help decision making. Peer reviews and social media have provided an easy to digest and readily accessible source of information.
The same is true in the B2B sense. And it’s one of the reasons that volume-based lead generation is getting harder to generate continued results from.,
A new approach
However, despite this acknowledgement of the need for change, there is still opposition, still resistance. One of the main reasons is that change is inherently risky. And nowhere more so than in the marketing environment where investing in new technology or software, and not being able to show return on investment is detrimental not only to business, but also to future revenues.
Marketing professionals need to be sure that the change is worth it.
Enter behaviour-based marketing
It’s true that marketers are already using programmatic marketing to target and attract new customers, but this needs to be taken a lot further. The approach needs to be more personalised, more focused and enable marketers to reach that crucial 2-5% of prospects that are actually looking to buy, ready to make that decision.
This new approach is very much a qualitative, insights-based approach. Instead of relying on the established generic “spray and pray” methods, marketers need to pay more attention to behaviour-based marketing that is fuelled by buying intent data, and is a way of transforming the quality of leads produced by marketing.
Behaviour-based marketing is so effective because it is able to accurately spot and take action on (often) elusive intent-to-buy signals demonstrated by the active <5% of the customer audience. This approach enables organisations to target this audience with pinpoint accuracy and create hyper-relevant messaging for it…in real time.
However, this is where the first hiccup may be experienced; instead of receiving 100 leads from a campaign, for example, sales will only receive 25. Immediately the question is raised, why so few? Last time we received more leads. The key differentiator here is quality. How many of those 100 leads actually panned out versus how many of the 25?
Marketing teams will be subjected to the age-old argument of quantity and quality. But when it comes to lead generation, volume often increases the risk of reducing quality, as energies are often driven by the need to deliver enough leads to satisfy demand.
Adopting a quality first approach may be easier said than done, especially considering the above, but the following stepped approach can help.
Best practice approach to behaviour-based marketing
Take a layered approach
By taking a tiered approach to define the total addressable market, departments can allocate most of the marketing and sales resources to those audiences that are most likely to engage.
Use a structured approach to learn where to place the most effort, where to cut ineffective activity, and how to identify those most likely to buy a lot quicker.
Recognise the buyers
Build a deeper understanding of customers by researching and mapping the actions and behaviours of the entire decision-making unit for each customer. In turn this helps build buyer personas and relevant trends.
Identify the active market
Through the right mix of context, relevance and timing, that small portion of the market that is showing current buying signals can be identified.
Context – Consider how best to layer multiple behaviour-driven insights around your customers and prospect organisations from within your own systems and third party buying intent platforms to reveal true intent
Timing – Gather insights in near time to establish the stage of the buying journey and the best fit persona to target. Buying journeys don’t last forever, so you need to react quickly.
Relevance – Prioritise your targets and ensure your messaging matches their needs, driven by behaviour and buying stage.
Behavior-based marketing is not just a theory. It enables organisations to seek out the right audience, with the right message, and at the right time. The sales team can focus on what they are good at; having meaningful conversations with customers about which solution best meets their needs, rather than if there is one.
Customer expectations are changing; this could be the way to meet them.
About the Author
Jon Clarke is CEO at Cyance, a predictive marketing technology and customer buying behaviour insight company. Jon previously led the strategy to transform Cyance from a b2b demand generation agency into a private equity backed predictive analytics technology business. He has a passion for innovation and technology when both collide to make life more interesting and productive.
Jon has over 22 years’ experience in sales, b2b marketing and business strategy and has worked with brands such as; Pitney Bowes, Zebra Technologies and Nokia. Helping them to transform how they deliver marketing using next generation marketing and advertising technology fuelled by cleaver data.