The Sales Hierarchy of Lead Data Needs
Table of Contents
- The Sales Hierarchy of Lead Data Needs
- Why the top of the pyramid matters
- Making sense of unstructured data
Businesses both large and small are putting into place ‘Know Your Customer’ programs, where they are capturing and leveraging customer data to optimize marketing, sales and service efforts.
Compared to even a few years ago, the amount of prospect and customer information available to sales reps has increased significantly to the point where they can tell not just your buyer profile and onsite interaction history, but also what you’ve been doing on your social networks. And yet – we know that sales continues to be an uphill endeavor.
According to CSO Insights, 42% of sales reps feel they do not have the right information before making a sales call, whilst nearly half of companies report that their sales reps need help figuring out which accounts to prioritize. Salesforce’s own research has shown that 92% of all customer interactions happen over the phone, with 85% customers reporting being dissatisfied with their phone experience.
Each of these stats belie an inconvenient truth: despite having access to some of the best technology in the world, sales reps still lack the right information to successfully engage and convert, upsell and/or cross-sell their prospects and customers.
With that in mind, and a knowing nod to Dr Maslow, we’ve created ‘The Sales Hierarchy of Lead Data Needs’ to help our clients drive revenue from a more mature customer data strategy.
The Sales Hierarchy of Lead Data Needs
This pyramid shows the different levels of lead data that are captured, stored and used as part of customer management.
Contact details: This is the most fundamental element of a lead — it constitutes an email address (although a telephone number is desirable). These are the “hygiene factors” that Maslow spoke of — the most basic requirement for customer management. Without it, no other data is useful.
If our marketing function hands over a lead without contact details to our sales team they will reject it — probably laughing in disbelief as they do so!
Firmographic data: Currently a B2B obsession, firmographic data refers to information such as a job title, name of company the lead works for and the sector or industry. Other derivative information might also include the revenue band of the company, the size of the company, where it is based and so on.
Firmographic data is now appended to most leads in a B2B environment, either manually or through a growing range of specialist data providers. It becomes very useful when prioritizing leads — particularly if a sales strategy requires targeting prospects within certain sectors or businesses, or with particular job titles.
Product holding data: The volume and variety of this data completely depends on the type of business. For travel & hospitality providers it might include every hotel room you have stayed in, and flight you have bought. For a telecommunications provider it might include your data plan, usage, and handset. Anyone looking at this will know not just the lead’s contact details and the profile of the company they work for but also what this customer has previously bought.
Interaction data: This data helps you understand how engaged this person is with your organization’s marketing and product.This can be captured and updated into your CRM system by marketing automation tools such as HubSpot, Pardot and Marketo.
Interaction data is most commonly held in the form of a ‘lead score’ — a cumulative figure based on the number of engagements with a company’s website or email program. If you’ve had lots of engagements, you’ll have a higher score. To that effect, it is quite a blunt measure but is also helpful way of prioritizing the hottest leads.
Interest data: As an individual engages with your organization across different touchpoints and channels they leave a trail — a digital footprint or digital body language — from which you can infer their interests and likely purchase intent. Interest data isn’t comprised of information the customer has explicitly told you — it’s inferred based on their behavior.
The way we capture interest data is through looking at how buyers engage with content. Content is integral to the research process and as each prospect engages with client blog-posts, white papers, product pages, email programs and social media these content engagements are highly revelatory of their interests and predictive of what they’re likely to purchase in the future.
Since interest data reflects an emerging and ever-changing lead context, it is constantly updated as the prospect or customer consumes a new piece of content, or exhibits a new behavior. The outcome is that salespeople know what to say, before they even pick up the phone!
Why the top of the pyramid matters
Marketers and salespeople are constantly driving forwards by looking in their rear-view mirror, i.e. using historic data that’s perhaps three months old, when they should be looking ahead at what their prospects and customers might or are highly likely to do.
There’s a whole slew of technologies that have been set up to use predictive analytics on lead data. Often this is limited to contact and firmographic details — but this is rarely enough data to make accurate or useful predictions. For a start, both of those datasets are very static; if I had the same job title and same contact details in a year’s time as I do now then my ‘likelihood’ to buy a particular product would be exactly the same. This is clearly wrong! There is a timeliness to my intent as a customer, despite what my firmographic or contact details may suggest.
This is why interaction and interest data are very important: they describe my emerging context — not just who I was, but who I am and am becoming. Unsurprisingly, this is becomes a very actionable dataset within the marketing, sales and service environment.
Making sense of unstructured data
The higher you go on this pyramid, the more dynamic the dataset, and the less structured it is. Harnessing interest data is a massive challenge. As Marc Benioff articulated at Dreamforce 2014, unstructured data now outweighs structured data 5-to-1 within the Salesforce ecosystem.
That said, it is a challenge that can, and is, being surmounted. In the marketplace, we see a process of maturity — building from the bottom to the top of this pyramid. Marketers and salespeople in developed and mature organizations have solved the few rungs and are looking to work with and structure interaction data, and then learn about and predict interest and intent, to gain more accurate lead context.
This is how you truly ‘Know Your Customer’: understand their interests so you can better engage them. This is the way to differentiate and gain an edge in the marketing, sales and service environments, in an increasingly competitive and customer-obsessed world.
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