Let’s face it, we’ve all done it. In our zeal to latch onto the sales and marketing bandwagon effect: a phenomenon whereby the rate of uptake of beliefs, ideas, fads and trends increases the more that they have been adopted by others. Now, Intent Signals are neither new or a fad. History and experience have established that Intent Signals are a viable demand generation strategy. Savvy B2B sales and marketing teams must put Intent Signals in relative context by using other data factors that may or may not include psychographic, geographic, and firmographic information. In fact, as long as there have been sales and marketing organizations, there has been a fervent quest to decode when and why prospects make purchasing decisions (i.e. to squeeze every droplet out of end-of-the-year budgets, actual necessity, avoidance of obsolescence or to take advantage of promotional or discount opportunities).
To be fair, the thirst for Intent Signals is certainly easy to understand. Just a decade ago, marketers were limited to elementary research options such as focus groups, brand studies, surveys and anecdotal “evidence”. (Compare that to today’s evolved marketers that can apply analytics, third-party data, social media content, and first-party financial information.) Fueled with deeper data sets and improved data techniques, B2B marketers are now able to determine more meaningful insights with intent signals.
However, as everything else in life, gaining insight into prospect or customer purchasing behaviors isn’t as simple as hitting a button and having a computer spit out relevant, in-market prospects. Recent studies have determined a great many CMOs have stated that data analytics are one of the biggest challenges they face. So, what are the most common pitfalls sales and marketing teams face when working with Intent Signals? Buckle up, we’ll share a few landmines to try and avoid at all costs:
1. Never, never, never forget context
Intent Signals only count if there is a clear understanding of their definition and purpose. Without this knowledge, marketers and sales teams are rendered powerless in affecting outcomes. Even at the onset of data exploration, marketers must establish methodologies and processes that include detailed explanation(s).
For instance, let’s imagine a business intelligence company correlates online opinion about the accuracy of their data, both good and bad, the more sales sag. In this instance, are the opinions of potential prospects indicative of intent? Is this even a useful indication of intent? Are sales in decline because the subject matter is uncomfortable for the prospects, or because they are confused on how to market to their target base? Without knowing the answers to these and other similar types of questions, how can the BI company know for certain if there is a problem with their algorithms? Or, is it an issue of unrealistic expectations or the result of faulty marketing messages? Does the answer lie in retooling the service or revising their brand perception? Without an understanding of true prospect intent, the results may prove to be completely off-base.
2. Don’t confuse action with intent
Let’s briefly clarify our terms. The word “intent” should be interpreted to mean “intent to purchase.” Intent metrics must be tied into revenue in order to produce demonstrable ROI estimates. Don’t be lulled into a state of lead bliss by taking a look at bounce and click-through rates. By themselves, this information doesn’t automatically assume intent. Prospect or account purchasing behavior only count if they are measured and correlated to revenue.
Data shouldn’t be used only to track market share, brand viability or to prove “gut feelings” or current trends. Data is too valuable to blow on ego or raw hunches. Data should be tracked so insights can be considered actionable. Remember, Intent Signals must include metrics that are rooted in revenue. Most importantly, actionable Intent Signals must be able to produce, you know, action on the part of the prospect or account. In other words, what prospect or account behavior do you want them to engage in? What does the ROI analysis reveal? What is the cost of the action and what are the positive outcomes?
3. You know what they say about assumptions
Every B2B marketer or sales executive worth their salt wants all the secrets of their target prospects as soon as possible. To make assumptions (even those based on years of experience) is unscientific at best, and dangerous at worst.
For intent methodologies to be truly effective, B2B marketers need to know exactly whose intent they are measuring. Is it their existing account base, targeted prospects, , or even pockets of potential customers that haven’t been exposed to the brand as of yet?
For instance, a brand whose business comes primarily from state and county engineers will monitor intent among this category of prospects. This means the brand will need data processes in place that provide this level of geographic granularity. But the brand should never make assumptions, in the event that Intent Signals come from other locations other than state capitals or county headquarters. If the brand has failed to monitor potential prospects outside their known base, they will be in danger of missing potential opportunities for new growth.
4. Don’t cheat by stacking the deck in your favor to support your hypothesis
For example, this can be tempting to do after analyzing the results of a demand generation campaign you believed performed well. You also discover that the landing page conversion rate ranked better than average. You use this information as your sole data point, whereby you ignored the fact that none of the leads generated were qualified or that traffic to the landing page sucked air. Tsk tsk.
Although this tact can be tempting, never approach data exploration with an anticipated or hopeful conclusion in mind. Rather, find a particularly annoying associate who always likes to contradict your opinions as a “devil’s advocate”. Honest, lively debate is a good thing and helps eliminate the kinks in an argument or when defining a strategy.
5. Just the facts, Jack!
When dealing with mounds and mounds of data, it’s easy to be distracted or misinterpret the data that surrounds you. Focusing on data that is irrelevant can send you down the wrong path. In the age of big data and Intent Signals, it’s an all-too-familiar problem.
For instance, you’re in the midst of assessing the effectiveness of a social media campaign as it relates to generating leads. Although the campaign clearly generated a ton of followers, you naturally make the assumption that the campaign was extremely effective. One problem though. The campaign didn’t generate any leads. Bummer!
Instead, establish data analytical boundaries. Take into consideration time, resources, and metrics. So, if you’re trying to determine conversion rates on a landing page during a social media campaign, make sure you define the time frame of the campaign, as well as visits and leads from the exact landing page being analyzed. Only traffic from that social media campaign will be used to answer the conversion rate question. By adopting a strict parameter discipline, you can hedge your bet in not getting distracted by bad data.
The bottom line…
If done correctly, intent-level data gives B2B marketers the ability to become data-driven, better understand prospect pain points, and make smart, insightful, and strategic decisions early in the buying cycle.
According to research from Forrester, most marketers haven’t been able to capitalize on intent signals’ promises. In fact, 74 percent of firms say they want to be “data-driven,” but only 29 percent say they’re good at connecting analytics to action.
Buyer intent, at the first sign of target account or prospect interest, (while buoyed by automated actions) provides the seller with the advantage of staying ahead of the competition and finally delivers on the promise of Intent Signals.
Look for Part Two of our blog series on avoiding unintentional mistakes with intent signals soon. For more information on Intent Signals, please visit our website at www.trueinfluence.com.