Scaling Personalization with Marketing Analytics Staffing

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Established in 2004, B2B Marketing is now the number one, go-to resource for marketers in B2B across the globe.

Right from the start they had a clear mission to actively empower marketers and leaders to drive serious business growth. The online publication does this by delivering strategic guidance, skills, and inspiration, drawn from the latest real world examples of business to business marketing at its very best.

Personalized marketing at scale is set to become a game-changer for B2B. The convergence of predictive analytics, intelligence-led content creation and marketing automation is unlocking possibilities the sector could only dream of a decade ago.

But for many brands, data quality will be a limiting factor. Unless action is taken, it could put a stranglehold on the scope and scale of future marketing success.

Scaling Up 1-1 Messaging

An article in The Guardian earlier this year considered large-scale personalization from a consumer marketing viewpoint:

In essence, personalized marketing at scale is the ability to reach different consumers with different creative messages, rather than having to have a single TV advert that everyone sees. It means you can subtly tailor your executions based on demographics, interests, location or even purchase history, reaching millions of consumers but each with something that seems personally relevant and interesting.

In a B2B context, large-scale personalized marketing goes even further. It enables you to target different types of decision maker with tailored messages relevant to buyer journey stages. It’s inherently complex, but with today’s technologies it is also inherently achievable.

Where Data and Marketing Analytics Staffing Come In

Data and talented marketing analytics staffing are the cornerstones of personalization. It infiltrates every aspect of the process, and the most polished marketing activity can unravel if underlying data is not up to scratch.

At a strategic level, data surrounding purchase history is a powerful indicator of a prospect’s propensity to be in the market for a product or service at a given time. Take the technology sector. If you know when an organisation invested in a particular solution, you can make assumptions about its circumstances and predict pain points it may encounter in the future. This insight can inform the development of content that addresses these problems, subtly raising a flag for additional solutions or services.

Today’s marketers have the tools to precisely tailor what to say, when to say it, how to say it in the most appealing way. And yet, even with all these capabilities, many marketing endeavors are flailing because of shaky data. There is little point investing in sophisticated analytics and automation if your data is fundamentally flawed.

Verifying Data Quality

Most marketing directors and CMOs will admit that maintaining data is a bit of headache. The reality is that their departments are stretched and people-hours are spread thin. It’s easy to neglect back end processes like data housekeeping and focus on more visible activity.

However, maintaining data is one of those jobs that you have to keep on top of all the time. Think of it like cleaning the house. It’s no good having a spring clean once a year if you don’t bother washing the dishes for the next six months.

We all know that data can never be 100% perfect. Natural churn is inevitable, but its impact can be mitigated with regular care and attention. For enduring marketing success, basic data management has to move up the agenda – and stay there.

 

 

Read the entire article on B2B Marketing Blog


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