7 Ways to Use ion Data in Marketing Automation

 Justin Talerico, ion interactive's CEO and cofounder
Justin Talerico, ion interactive’s CEO and cofounder

I’m a content marketing data geek. I love earning and using authentic and accurate data that describes our buyers. Here’s how we do that…

This is about focusing marketing and sales resources on buyers who are most likely to produce revenue.

Here are 7 ways ion leverages interactive content marketing data in marketing automation:

1.     Segmentation — for marketing

WHY: Marketing automation systems are often home to thousands of leads. In order to deliver more relevant nurture streams, smart marketers break their universe into addressable segments. ion facilitates high fidelity segmentation from explicit rather than inferred data.

HOW: Assessments, report cards and conversion paths are among the interactive content marketing experiences that yield explicit segmentation data. We combine all that rich data from buyers’ answers to strategically designed questions into a single ion mashup field exported to the MAP. We then use our marketing automation platform (MAP) to scan our ion mashup field for high qualifying answers and then add matching buyers to segment lists. We also tag those buyers for easy reference in the MAP.

2.     Best Bets — for sales

WHY: Sales needs a helping hand to identify their best bets. ion is uniquely suited to provide descriptive data that can be pattern matched to surface best bets based on explicit data from their interactive journey.

HOW: The digital journey can be a long one — with many touchpoints from form submits, to eBook consumption, to self assessments, to solution building, budget calculating and so on. The amount of high fidelity data generated over the course of that journey is both awesome and intimidating. ion provides quique, explicit data for marketing automation pattern matching. We use rules in ion and the MAP to look for combinations of responses across touchpoints that indicate ‘best bets’ for sales. For example, a buyer may respond that they have budget in one touchpoint, that they have pain in another touchpoint, and that they are the decision maker in another touchpoint. By having an automation rule look for that pattern in the data ion pushes into the MAP’s mashup field, we can surface ready buyers to sales. Marketing also uses ‘best bets’ as their most senior segment for judging performance — meaning, if marketing efforts don’t perform well with ‘best bets’, then there’s a marketing problem to solve.

3.     Worst Bets — for sales (and marketing)

WHY: Because where there are ‘best bets’ there are ‘worst bets’, and getting the worst bets off your radar minimizes distractions and consumption of your resources. Meaning, you need to segment out your ill fits so that you don’t waste time and money catering to them.

HOW: By the same token as ‘best bets’, certain combinations of buyer responses in their interactive journey indicate that they’re likely to be a waste of time. For example, they may indicate that their industry is outside your target, combined with their company size being an ill fit, combined with an indication of not having budget or decision making authority. And it’s likely that these data points come from various touchpoints across the journey. We use marketing automation to look for negative response patterns in the ion mashup data field and to segregate those matching leads so that sales doesn’t waste resources on them. Marketing also segments ‘worst bets’ out of its core group for evaluating performance — because we care a lot less about how ill fits perform.

4.     Targeting — for marketing

WHY: Relevance drives results. When each subsequent touchpoint in the digital journey can be smarter and more relevant, the journey accelerates revenue and business value improves.

HOW: Certain types of ion experiences earn explicit data perfect for targeting. Great examples of relevance targeting include gender, industry and seniority. Gender may come from a data append service and get immediately attached to the buyer’s ion record. Rather than inferring industry or seniority, we may get that data explicitly using a conversion path, segmenting eBook or report card experience. We write targeting data into the ion buyer profile and use that to make subsequent experiences dynamically more relevant. Rules within ion make that dynamic relevance possible. We also send targeting data to the MAP and use automation rules to segment and tag. We can then more specifically nurture and sell using those segments and tags to target messages, emails and experiences.

5.     Personalization — for marketing and sales

WHY: Personalization is like a more intimate form of relevance. Helping people to feel known and understood can make them feel more comfortable and willing to interact. Eliminating redundant personal data collection (and friction) is key. A word of caution — personalization taken too far is just creepy. Don’t cross that line and all is well.

HOW: ion creates a buyer profile for each user and appends that profile over the course of their journey. At some point an anonymous lead becomes known when they engage in touchpoints that yield their personal information. A typical interactive journey includes many of these touchpoints. The keys here are to only ask for data once, to ask for few data points at any one time, and to ask for new and deeper data in subsequent visits. This is like a much smarter and smoother version of ‘progressive profiling’. Later visits use previously supplied personal information to dynamically greet, subtly enhance and eliminate data gathering redundancies. For example, ion dynamically changes fields shown in forms based on what’s already in the buyer profile. Forms dynamically shrink making follow-on conversions more likely. Profile data is also passed into the MAP and leveraged in nurture programs.

6.     Scoring — for marketing and sales

WHY: Scoring sorts the wheat from the chaff. Inferred scoring — based on digital body language of clicks, downloads, views, opens — is guesswork subject the sub-optimal accuracy and noise. ion provides explicit data that minimizes guesswork and improves the accuracy and reliability of MAP scoring programs.

HOW: Buyer responses from their interactive journey are saved to their ion profile and simultaneously sent to the MAP as part of the ion mashup field. Automation rules in the MAP increment or decrement the explicit side of the lead score based on a buyer’s explicit responses to questions across their journey. A typical scoring challenge is a glut of low fidelity behavioral data (busy data) and a dearth of high fidelity explicit data. ion reverses this, supplying a glut of high quality, high reliability explicit data. This enables scores to climb more rapidly and accurately, accelerating lead scoring programs and ultimately pipeline velocity.

7.     Full Circle — for marketing

WHY: So far, the first six ways to use ion data in marketing automation have focused on leveraging ion’s high fidelity information in the MAP. Well, it works the other way too and the business value is enormous.

HOW: ion’s experiences can dynamically change based on data passed in from marketing automation platforms. The code-free rules that enable this magic can consume everything we’ve talked about above — segments, targets, personalization, scoring — and make the user experience more relevant, personal and effective in real time. This high fidelity dynamic relevance is the wind beneath the wings driving acceleration of the journey and the pipeline.

So there you have it…

Some people call it ‘data driven’, others ‘data inspired.’ For ion, the focus is on the integrity of the data doing the driving or inspiring — and on putting that data to work. Starting with explicit, descriptive data collected in a useful interactive journey means that our seven ways are accurate, authentic, reliable and most of all effective. It’s all about results.

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