Intent Data for Account-Based Marketing:Diamond in the Rough or Just Plain Pixie Dust?

FORWARDIntent data has recently attracted the business marketing spotlight for the simple reason that technology makes more of it available than ever before. But as this ebook points out, intent data is not a cure-all: it finds just a portion of active buyers, and must be used with other information to gain a full picture of the buyers it finds. On the other hand, intent data can be used in many ways beyond identifying prospects. So its value to marketers is substantial.

Marketers need to understand all these nuances to make the best possible use of intent data. This ebook does an excellent job of describing where intent data comes from, how it can be applied, and where it fits into marketing and sales processes. Any marketer struggling to make sense of the noise surrounding intent data will find it an excellent place to start.

David Raab Principal Raab Associates

INTRODUCTIONWhat is intent data?

There are a few different definitions, but at it’s core, intent data helps businesses identify which prospects are actively searching for a particular solution, but haven’t yet reached out to their company to start a sales cycle. And in just a few short years, intent data has become the darling of the B2B marketing world.

Intent data provides an indicator of a company’s willingness to engage with you. The stronger the signal, the more likely they are to respond to your outreach. Why is that? Because intent data shows which companies are actively interested in a particular topic or solving a particular problem. It is a time-based signal that, when used with predictive scores for your leads and accounts, will let you figure out when the best time is to reach out to the account.

Intent data shows businesses which prospects are actively searching for a particular solution, but haven’t yet reached out to their company to start a sales cycle.

INTRODUCTION

When used properly, intent data is incredibly powerful and has the ability to make marketing and sales more efficient. After dominating the B2C world, it broke into the B2B marketing scene as the silver bullet that many people thought would fix all their demand gen issues. Making sales and marketing efforts more effective will increase the revenue of any business, and companies were chomping at the bit to understand exactly when a prospect was ready to purchase a particular solution.

However, intent data isn’t a silver bullet. Some people think raw intent data is like an uncut diamond – it’s valuable, but it has yet to achieve its true potential. These people believe companies need to understand how to properly transform, analyze and use intent data to maximize its effectiveness, in the same way that a jeweler polishes and cuts a rough diamond to uncover its hidden beauty. Others think intent data is like pixie dust, you can just sprinkle it onto anything and improve your outcome, regardless of whether the original item was good or not. Lattice Engines falls into the diamond in the rough camp, but intent data is still a new enough tool in the B2B world, that this argument is likely to continue for a few more years.

Willingness to Engage

Window of Receptivity is Narrow

Time

INTRODUCTION

We are now in the next stage of intent, where B2B companies are becoming more sophisticated in how they use intent data.

Amongst our customer base we’ve seen strong correlation between the strength of the intent signal and conversion rate. Solution providers are now integrating intent data with other types of data and creating sophisticated predictive models that can show businesses, in real-time, which prospects have an active interest in their solution. Once companies can see this level of detail, they can utilize it in a number of marketing and sales programs, and start seeing positive correlations between the strength of an intent score, and the conversion rates of their funnel.

Intent Strength Score

Con

vers

ion

Rat

e, %

Con

vers

ion

Rat

e, %

Intent Strength Score

LATTICE CUSTOMER 1

LATTICE CUSTOMER 2

INTENT DATA 101Intent data tells what content companies searched, engaged with and consumed

Let’s take a step back – intent data indicates whether or not a prospect is interested, and actively looking for a solution to a problem they have, but how do you find and identify those signals? Intent is aggregated from multiple sources, because it’s expressed in multiple ways:

ONLINE(ON-SITE) OFFLINE

SEARCHES, FORUMS, BLOGS, AD CLICKS, ETC.

ANONYMOUS INTERACTIONS ON BRAND-OWNED PROPERTIES, (E.G.

YOUR OWN WEBSITE). ETC.

3RD PARTY EVENT ATTENDANCE, OFFLINE

PURCHASES, ETC.

ONLINE(OFF-SITE)

INTENT DATA 101

When analyzed properly intent data can show you the prospects that are interested in purchasing your solution right now. However, only when it is combined with other types of data, such as firmographics or technographics, can it show companies a full picture of what is happening at their account—and can provide true predictive insights.

For example, 10 different people from the same company may be searching for a solution your company sells, which shows high intent. However, what if the company is in the education industry, which you don’t sell to at all? You’ll wind up reaching out to the company only to find out that its not a good fit, and will have wasted precious marketing and sales resources.

SCALE ACCOUNT-BASED MARKETING WITH PREDICTIVE ANALYTICS 12

Includes financial/risk profile about the

company, structural profile, IPO filings, new

office openings, new executive hires and

other company events, etc.

Includes technologies installed behind the

firewall, shopping cart software and other

website technologies, network profile, etc.

Includes prior products purchased,

shipments, financial contracts, periodic

spending with brand, etc. (applies to

modeling existing customers)

Includes responses to campaigns, sales

interactions, support activity, product

usage, ad clicks, searches, 3rd party content

downloads, etc.

Includes trends in quarter-over-quarter

revenue, profitability, hiring, Adword spends,

etc.

FIRMOGRAPHICS TEC

HN

OG

RA

PH

ICS

TR

AN

SACTIONAL BEHAVIOR+INTEN

T

GR

OW

TH

TR

END

S

b) Enrich personas with account-level insights

Buyer personas are the foundation of any targeted marketing strategy. Done right, personas are a very powerful tool for really understanding your buyers, the questions they ask, and the journey they take in order to identify and solve their problem.

Account-based marketing relies on account-level insights to add important business context to your buyer personas and provide a true 360-degree view of your targets.

The important point here is that while you are targeting companies, you are still selling to people – in fact, you’re typically selling to a committee in B2B. The key is to identify the different titles/job functions involved and understand their role in the buying process. For instance, if you’re selling marketing automation software, the CMO may well be the economic buyer while the VP Ops may be a key influencer/evaluator. IT, on the other hand, may be responsible for vetting a solution’s compliance with organizational security and privacy policies.

Figure 5: Examples of key buyer attributes that can be surfaced by predictive analytics

INTENT DATA 101

That’s why its critical to combine intent with other data, such as firmographic, fit and technographic, to make sure the prospect looks like your ideal customer and is actively interested in your solution. When all this data is combined together, predictive marketing and sales solutions can make an immediate impact on bottom line of a business by predicting who will buy, what they’ll buy, and when.

Includes responses to campaignes, sales interactions, support activity, product usage, ad clicks, searches, 3rd party content downloads, etc.

Includes prior products purchased, shipments, financial contracts, periodic spending with brand, etc. (applies to modeling existing customers)

Includes technologies installed behind the firewall, shopping cart software and other website technologies, network profile, etc.

Includes financial/risk profile about the company, structural profile, IPO filings, new office openings, new executive hires and other company events, etc.

Includes trends in quarter-over-quarter revenue, profitability, hiring, Adword spends, etc.

TRANSFORMING INTENT DATATransform raw intent data to maximize its effectiveness

When raw intent data is properly transformed it provides valuable, deep insights that can help marketing and sales teams focus their efforts on the right accounts, using the right messages. However, you need to have a good understanding of what transformation you need to create in order to produce important and predictive intent signals. It’s vital to have processes in place, either through your company or through a solution provider, to properly transform intent signals from raw data to predictive insights.

RAW DATA PREDICTIVEINSIGHTS

INTENT SIGNALS

TRANSFORMING INTENT DATA

Intent data can be difficult to work with, because it varies in time, and that variability adds more complexity.

In order to properly utilize intent data in modeling, Lattice has created a ‘topic intent score’ to characterize how engaged a company is with a given business topic (i.e. how many companies show various amounts of intent for a particular topic). This score is a combination of overall company activity, intent topic density and any spike in interest for a given topic. This then enables us to characterize the distribution of the company universe, and identify the companies that actually have high intent for a specific topic, at a given point in time.

These accounts (many) are showing LOW levels of intent for Topic X

These accounts (many) are showing AVERAGE levels of intent for Topic X

SCORE DISTRIBUTION PER TOPIC20 topics from top 25% of topics by count; Black line is all topics

Latice Topic Intent Score

Den

sity

These accounts (few) are showing HIGH levels of intent for Topic X

TRANSFORMING INTENT DATA

In this manner, Lattice is able to classify what companies are actually showing intent, in addition to the level of intent they are showing. Using those algorithms, we aggregate billions of B2B intent signals every day, and compute an intent score for each company and topic, and then provide this information to our customers within their marketing automation or CRM systems.

Businesses can then segment and monitor prospective accounts based on their level of intent. For those accounts with high intent, companies can engage via high-touch programs, such as sales calls or field events. For those accounts with low levels of intent, companies can put them into a nurture campaign, or other lower engagement programs.

• Once intent data has been transformed from raw signals into specific insights, teams can easily drill down to see what companies are showing very high levels of intent, on particular topics.

• These granular insights can then be put into action by sales and marketing teams through their existing workflows.

Intent Topics

Topic A Topic B Topic C

Company A Very High Very High Very High

Company B – – –

Company C High Very High Medium

TRANSFORMING INTENT DATA

The diagram below provides sample framework for how you can use a combination of predictive score and intent signals to drive very targeted outbound tactics.

LEAD/ACCOUNT PREDICTIVE SCORE(How likely are they to do business with me?)

INTE

NT

SIG

NAL

STR

ENG

TH(H

ow in

tere

sted

are

the

y rig

ht n

ow?)

HIG

H

HIGH

LOW

LOW

Example Tactics:

• Run targeted ads

• Invite to executive dinner

Example Tactics:

• Send to sales for outreach

• Run targeted ads

Example Tactics:

• Add to standard nurture track

• Potentially ignore?

Example Tactics:

• Add to standard nurture track

PRACTICAL APPLICATIONS FOR INTENT DATAIntent data has numerous practical applications within predictive marketing and sales activities. It makes account-based campaigns much more effective by allowing teams to identify accounts that are actively looking for a solution, and use granular intent data to tailor their messaging for those specific accounts.

Lets walk through how one of our customers, an enterprise back-up and recovery solution, uses intent data from Lattice to super-charge its account-based marketing activities.

Every two weeks the company pulls in a list from Lattice of companies that are showing high intent in key topic areas such as online back up and data recovery. They then segment the companies based on fit, behavior, company size and technology attributes.

This segmentation dictates which 4-touch email nurture stream a prospect will be filtered into. As soon as a contact clicks a lead in any of these emails, they are automatically added to a targeted advertising program through Demandbase, through which they were served up relevant ads with the same messaging as the emails.

PRACTICAL APPLICATION EXAMPLES

On the sales side, once the first email goes out in the nurture campaign, a sales development representative reaches out and calls key contacts at the account.

Using details from the intent signals and other account insights, they tailor their call script based on the customer’s interests, company size and technologies that are already deployed.

For example, has the company expressed interest in enterprise security? Perhaps the SDR should lead with a message around how their offerings provide best-in-class enterprise security capabilities. With this level of integration, both marketing and sales are serving up the same customized messaging and offers to key accounts in a coordinated effort. They were able to take immediate action on real-time interest from their customer base, which drove increased conversions and improved the velocity of their sales pipeline.

PRACTICAL APPLICATION EXAMPLES

Intent Topic Number of Content Sources Total Views Unique Users Zip Code

Security 60 12 11 95594

Content Distribution Networks 59 29 29 33135

Telecom 128 26 4 33122

Private Branch Exchange (PPX) 103 26 26 33128

Predictive Dialing 87 18 21 33122

Phone System 78 13 13 33128

0 10 20 30 40 50NUMBER OF UNIQUE VIEWS BY TOPIC DURING THE LAST 6 WEEKS

Endpoint SecuritySecurity Tools

Application SecuritySecurity

Data SecurityWeb Service Security

Internet SecurityNetwork Security Appliance

Managed Security ServicesSecurity Management

Security EventWireless Security

Security MonitoringEmail Security

Security Architecture

4130

2929

2522

2119

187

55

433

0 10 20 30 40 50

PRACTICAL APPLICATION EXAMPLES

Another great opportunity provided by intent data is the level of granularity it can show. An enterprise security vendor worked with Lattice to determine the varying levels of interest and intent its prospects were showing for more than ten different kinds of security topics. This enabled them to make the content in their marketing programs very specific, and target the right accounts with the exact right message.

Another practical use for intent data is determining where to hold field-marketing events. A telecommunications provider was able to map which of their accounts with high predictive scores are also showing high intent signals using zip codes. Based on that information they only scheduled field events in areas where there was a large concentration of high scoring accounts that also had high levels of intent data for multiple topics of interest, in this case network security and telecom.

PRACTICAL APPLICATION EXAMPLES

Example Technology Topic:"NETWORK SECURITY"

Example Telecommunications Topic:"TELECOM"

Two clusters of states:1. States with similar level of intent concentration for both topics: e.g. California, Illinois, New York2. States with different level of intent concentration for both topics: e.g. Michigan, Minnesota, Florida, Colorado

INTENT SIGNALSIntent signals can be infrequent but incredibly valuable

While harnessing intent data is extremely beneficial for companies, as we’ve seen in the earlier examples, the one drawback is that intent data is not always available within a given market segment. Why not? Well, employees of companies may use multiple devices to browse and search the web (their mobile device, their home computer, their work computer) and as a result, companies may not capture all the intent signals for a particular company or contact. Additionally, third party intent data is typically anonymized at the individual level for privacy purposes. So while you may know that 10 people from GE are interested in enterprise security, it’s difficult to discern if they from different buying centers or the same buying center (e.g. GE Capital or GE Turbines & Engines).

Based on research that the Lattice Engines data science team has done, fewer than 2% of companies demonstrate high intent for a specific topic at a given time.

2.0%

1.7%

0.9%

0.4%

Networking

Telecommunications

Security

Cloud

18%

14%

13%

4%

ANY Intent Strength HIGH Intent Strength

1. In the Universe of 500-4,000 Employees Companies during the last 6 weeks

% C

OM

PAN

IES

WIT

H IN

TEN

T SI

GN

ALS

1

For example (figure A), a Fortune 500 global communications provider wanted to include intent data in their predictive marketing and sales models. They looked at a set of 40,000 prospective accounts to determine what intent signals they were showing. Only 28% of companies showed any intent, and only 3% of companies were showing high intent for any of the four categories that were measured: security, telecommunications, networking and cloud. And that was just the 3% who were showing high intent at this point in time. This 3% will change over time, and new companies will appear with high intent, while other companies will have a drop in their level of intent.

INTENT SIGNAL EXAMPLE

Universe of Companies with

500-4,000 employees

Companies with Intent Signals1

during the last 6 weeks

32,756

8,236

1,031*

Figure A

* Only 28% Companies show intent signals

* Only 3% Companies show high intent

HIGH INTENT

MEDIUM/LOW INTENT

1. In the Universe of 500-4,000 Employees Companies during the last 6 weeks

This way the marketing and sales teams are able to focus the bulk of their energy, time and money on the most promising accounts.

This is why it’s crucial to add intent data to predictive models alongside other types of data, rather than relying solely on intent – often there isn’t much intent data available for a given topic.

However, when intent signals are there, they can be highly predictive, and contribute to increased conversions and revenue for companies. This Fortune 500 company is now able to set up high-touch engagements for that three percent of prospects showing high intent, while those with medium/low intent can be put into nurture campaigns to ensure they have awareness of the company. This way, the marketing and sales teams are able to focus the bulk of their energy, time and money on the most promising accounts. Less promising accounts will then be nurtured with relevant content, so that when they start showing higher-levels of intent, they’ll already be aware of the communications provider.

INTENT SIGNAL EXAMPLE

CONCLUSION: THE 360 DEGREE VIEWIntent data in predictive modeling gives companies a deep understanding of what their customer is interested in, which can then be used to enhance targeted marketing and sales activities.

And just like a diamond in the rough, to maximize your success using intent data, companies need to transform the raw, original object into something even more valuable. Intent signals are important but they’re not the silver bullet that will fix all of your demand creation problems. Adding intent data to the other data collected on prospects, such as technology attributes, firmographics and behavior, enables companies to get a 360 degree view of their customer.

This 360 degree view is the real silver bullet in marketing and sales. If companies get a clear picture of who their target customer is, and when they’re in market, they can make marketing and sales campaigns more contextual and relevant, creating instant improvements in their bottom line. So after all this, do you believe in pixie dust, or are you going to start looking for the diamond in the rough?

Lattice’s complete set of marketing and sales applications predicts who will buy, what they are likely to buy and when. As the market leader, Lattice’s proven applications combine billions of buying signals and apply advanced machine learning to help drive predictable marketing and sales performance. Companies of all sizes including Dell, Staples and SunTrust Bank use Lattice to deliver proven value, ultimately resulting in increased conversion rates and accelerated revenue growth. Lattice has headquarters in San Mateo, California.

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