Your dirty little data

No digital program in modern marketing can be truly successful without harnessing the power of big data. But most B2B marketers already know this so I'm not going to preach the benefits of data - you're already converted. The problem is if you're like most other B2B brands, you're awash in a sea of data. But even an ocean of data isn't going to generate demand if you’re drowning in it.

With AI and machine learning algorithms becoming readily available in many of the tools in your martech stack, the analytics available to us have gotten quite good, yet some marketers still struggle to answer questions like:

Which channel is having the most influence throughout the buying cycle of my target account list?

What is the value of the different digital touchpoints and how do they impact opportunities and revenue?

Why predictive analytics is a big deal

As a B2B marketer you likely have lots of data over multiple systems. Website analytics, engagement data from your social channels, data from your sales and marketing cloud… but are you using all of your data sources to achieve a single source of truth around your prospective customers?

Let’s take your CRM as an example, At a basic level, the data it contains lets you track engagement and conversion rates. You might learn a few things like the number of leads that are opening your nurture emails.

But what if you connected your CRM data to your website analytics?

What if you use your website’s analytics to inform personalized messaging of your campaigns based on the solutions they have been browsing on your website?

What if you started looking at third-party intent data and used your marketing automation platform to automatically nurture accounts who are showing a high interest in your products?

The possibilities are endless and what we can do today is just the tip of the iceberg.

Predictive analytics models engrained in your tools help to uncover the buying signals that are submerged under all the noise. You can create links between all the data sets you own, as well as second and third-party data, to provide context around everything you do to help you create better and more relevant digital experiences for your prospects.

Let’s take a look at ways forward-looking brands are using their data:

Predictive Segmentation – Finding your next customers

Traditionally, customer segments were defined by the marketer and mostly based on assumptions. Today you can use real-time data to automatically segment audiences by using behavioral data and firmographic/technographic data to inform commonalities and trends to create new target segments. Product-based clustering uses signals to track buying trends and determine the right cross-sell and up-sell opportunities based on previous sales behavior.

Propensity Modeling – One step ahead

These types of algorithms allow you to anticipate your customer’s behavior. How likely is a customer to inclined to make a purchase based on previous digital behavior? Are there patterns in the number of emails opened, the type of content that was consumed, or the pages that they’ve visited on your website that will determine their inclination to close the deal?

The right place at the right time

When you combine the power of advanced attribution models and real-time intent data feeds to inform your decisions, you’re in a great position to anticipate your customer’s next move and intersect their journey with the right message at the right time.

I predict happier customers

Predictive analytics can help you make customers happier. Throughout a customer’s journey, you can match any action your business takes to its outcome. Use data-driven insights to increase foresight. The competition is only a click away, which is why you need to make your brand’s digital experience the best it can be.

Garbage in, garbage out

I get it, there's a real shortage of data scientists… not to mention you have to shell out a lot of cash to attract top talent. And predictive analytics sounds really complicated. It is complicated. But the great thing about predictive analytics is that the algorithms and machine learning capabilities are already built into the many platforms out in the market today.

Nowadays, for an affordable subscription, you can import data from your systems - social, web analytics, CRM and sales data - into a single environment. Most of the tools in your current marketing stack include open APIs and have built-in integrations with the leading platforms.

Your end of the bargain, however, is to keep your data clean and up to date and identify the right technology for your needs.

Remember: garbage in, garbage out.

Get in touch if you’d like to talk more about how predictive analytics can improve your next campaign.