{"id":8122,"date":"2024-07-11T16:48:51","date_gmt":"2024-07-11T16:48:51","guid":{"rendered":"https:\/\/tup.kxe.temporary.site\/why-b2b-marketers-get-their-signals-crossed\/"},"modified":"2024-07-11T16:48:51","modified_gmt":"2024-07-11T16:48:51","slug":"why-b2b-marketers-get-their-signals-crossed","status":"publish","type":"post","link":"https:\/\/okdesign.ca\/fr\/why-b2b-marketers-get-their-signals-crossed\/","title":{"rendered":"Why B2B marketers get their signals crossed"},"content":{"rendered":"


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Did you know that you have your own intent data? You don\u2019t need to buy it. If you are executing campaigns, especially in existing accounts, you have data that goes much deeper than you could buy.\u00a0<\/p>\n

You just know where and how to look for it. Once you find it, you will realize that what has been sold or said to you about \u201csignals\u201d isn\u2019t exactly true.\u00a0<\/p>\n

The reality of intent signals<\/h2>\n

As marketers, we\u2019ve been told that there is a connection between a \u201csignal\u201d of a prospect seeking information with their interest in your company or product and assumed that a response to an offer made could imply they\u2019re \u201cin the market to buy.\u201d<\/p>\n

This is how ZoomInfo describes intent data based on signal strength:\u00a0<\/p>\n

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\u201cDerived intent signals are a mix of first-party and third-party signals. These offer insights into behaviors<\/em> that indicate interest<\/em> in a company, such as ad engagement, web activity, topic engagement and technology use.\u201d<\/p>\n

ZoomInfo, \u201cWhat is intent data?\u201d<\/a><\/cite><\/p><\/blockquote>\n

As a result, we tend to think of this as an MQL. But this is where things break from reality. Again, from ZoomInfo:<\/p>\n

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\u201cIdentify interest: Purchase-intent signals<\/em> help identify which companies are actively researching your solution before they fill out a form on your site or engage with your sales and marketing teams.\u201d<\/p>\n<\/blockquote>\n

This is simply not true; it\u2019s an assumption. Unless you understand a buyer\u2019s personality, which would give you real insight into their behaviors and motivations, and you can observe this over time, you can not assume that they are \u201cactively searching\u201d for what you are offering because they have \u201cpurchase intent.\u201d\u00a0<\/p>\n

We have found only a small percentage (5-10%) of cases where this is true, and we have evaluated engagement and intent data across seven industries and thousands of interactions. You will find the same thing when you look at your own data.\u00a0<\/p>\n

Given that 5% of your targeted audience is in a buying cycle at any one time, this would make sense. But what is more interesting is what is in the 95% of data you aren\u2019t analyzing or buying.\u00a0<\/p>\n

Dig deeper: <\/em><\/strong>The false allure of B2B intent data<\/em><\/strong><\/a><\/p>\n

Analyzing your own engagement data<\/h2>\n

Here\u2019s what you need to know about analyzing your own engagement data. First, pull data from your sales and marketing systems at the account level. We\u2019re often so busy executing we rarely have time to look at what has happened in the past. You\u2019ll want to pull 12 to 18 months of engagement data based on the length of the sales cycle.<\/p>\n

Pull data on 10 accounts to start. They could be the 10 biggest or most important (based on pipeline value) accounts. Then, examine the following areas.<\/p>\n

Engagement over time\u00a0<\/h3>\n

This is an important metric because it\u2019s a measure of mindshare you have with a buyer\/contact. Look for how they have engaged with your outreach over the past 12 to 18 months.\u00a0<\/p>\n

Is it a \u201cburst,\u201d for example, a C-level engages multiple times in a month, or is it \u201cconsistent\u201d \u2013 a couple of engagements over a longer period of time?\u00a0<\/p>\n

Engagement time<\/h3>\n

How much time did they spend with whatever was offered? Was it milliseconds or seconds? This will help you understand their level of engagement. Are they glancing at what was sent or did they dig deeper?<\/p>\n

Engagement frequency<\/h3>\n

Did they hit one thing multiple times in one day and over a period of time? This may be an indicator of them forwarding information to others. It also gives you insight into who might be the \u201crouter\u201d of information inside the account.\u00a0<\/p>\n

Engagement offer\u00a0<\/h3>\n

What are they engaging with (i.e., what offer or outreach)? Are they looking at webinar invites, new case studies, reading the newsletter, etc.? Having 10 accounts will give you a real insight into what content really matters.\u00a0<\/p>\n

Dig deeper: <\/em><\/strong>Why B2B brands must focus on orchestrating meaningful customer engagement<\/em><\/strong><\/a><\/p>\n

Understanding the real meaning behind engagement<\/h2>\n

Analyzing your engagement data will help you understand if the audience is interested in your brand, solution or just what was offered.\u00a0<\/p>\n

Most times, it will be just the offer. But that\u2019s a great insight because it allows you to narrow down your activities to the things that matter to your audience.\u00a0<\/p>\n

Content offers a window for a salesperson to be viewed as valuable. Unfortunately, it doesn\u2019t tell you if the target is in a buying window or at a certain point in the buyer\u2019s journey.\u00a0<\/p>\n

Giving the sales organization insight into how and what audiences engage with lets them focus on starting a relationship. Through a better understanding of why people are doing what they are doing, it gets to their real motivations. The signal becomes insight.\u00a0<\/p>\n

For example, did they look at your upcoming webinar invite or user conference? How many times did they look at it? How many emails related to those events did they open? Did they attend the event? If they didn\u2019t, you now know they were interested.\u00a0<\/p>\n

This creates an opportunity for the salesperson to offer an on-demand version of the webinar or maybe a free pass to next year\u2019s event. They\u2019re building a relationship based on interest, not jumping to selling a solution they have shown no real interest in pursuing.\u00a0<\/p>\n\n\n

That is what is in your 95% of the engagement data that doesn\u2019t get analyzed. It tells sales who to spend their time with and how to start a relationship so they could one day become new customers.\u00a0<\/p>\n

<\/p>\n

\n<\/div>\n

Contributing authors are invited to create content for MarTech and are chosen for their expertise and contribution to the martech community. Our contributors work under the oversight of the editorial staff<\/a> and contributions are checked for quality and relevance to our readers. The opinions they express are their own.<\/em><\/p>\n


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