Omnichannel Demand Gen: Finance Audience Use Case

The last time I wrote on this topic, it was to relate the results of our omnichannel campaigns to a marketing audience and a finance audience. Regarding the latter, I shared that Brand 1 sought to reach their audience through a unified campaign that leveraged email, social, and display concurrently. It was a strong outperformer, and even I was impressed.

But I’d be remiss if I didn’t also illustrate how a different brand – Brand 2 – wanted to approach a similar finance audience. Brand 2’s offer is for finance and accounting professionals. In contrast, Brand 1’s solution is for FP&A execs.

In Brand 2’s case, we built the strategy with omnichannel expectations (especially after Brand 1’s performance).

The campaign flight was three weeks in duration, and the outcomes sought were a minimum of 50 MQLs and “impressions intelligence” of the target audience.

Here are the results:

FINANCE2 Demographics Report (in UTC)
Report Start: August 1, 2021, 12:00 AM
Report End: August 31, 2021, 2:47 PM
Date Generated: August 31, 2021, 2:47 PM
Ad Budget: $720.00
Campaign Duration: 16 days
Campaign Goal1 attained: 55 leads
Campaign Goal2 attained: 500,000 impressions
Total impressions: 927,923

We exceeded the desired MQLs goal by 10% and drove 180% of the impressions we committed to them. Again, we can assemble this intelligence from company name, industry, location segment, function/level, and job title. An example of location segment:

Location Segment
% Impressions
New York City Metropolitan Area 130986 14.12% 15
Greater Boston 49428 5.33% 13
Greater Chicago Area 39556 4.26% 12
Los Angeles Metropolitan Area 54624 5.89% 5
San Francisco Bay Area 46701 5.03% 4
Dallas-Fort Worth Metroplex 28852 3.11% 3
Washington DC-Baltimore Area 25443 2.74% 2
Greater Philadelphia 22695 2.45% 1

For this same brand, we executed a concurrent email campaign that resulted in 100 leads. Aggregate campaign outcomes with 50% greater client budget? One hundred fifty-five leads and “impressions intelligence” for nearly 1 million unique records.

Here, it was all About the Persona

Unlike Brand 1, where we applied an expansive ABM list, Brand 2’s campaign was persona-driven. They needed to reach finance and accounting professionals, specifically in financial services-related industries, at companies employing 200+ people.

How’d do you think we did? Below are a few samples of the campaign’s performance. These data points are part of the unified information we obtain from an email channel and a LinkedIn Ads channel.

Company Industry Segment
% Impressions
Financial Services 233778 25.19% 17
Banking 57892 6.24% 8
Staffing and Recruiting 173814 18.73% 7
Management Consulting 83265 8.97% 6
Construction 46136 4.97% 6
Insurance 65018 7.01% 4
Human Resources 31693 3.42% 4


Company Size Segment
% Impressions
201-500 employees 160171 17.26% 13
1001-5000 employees 90041 9.70% 10
10001+ employees 117633 12.68% 10
501-1000 employees 90658 9.77% 9
5001-10000 employees 39756 4.28% 3
Job Function Segment
% Impressions
Finance 453650 48.88% 31
Accounting 107208 11.56% 18
Operations 154484 16.64% 6

By the way, the total data we can assemble includes “impressions intelligence” for a company name, industry, location segment, function/level, and job title. Here’s a taste of persona-based targeting outcomes:


Company Size Segment
% Impressions
10001+ employees 253346 25.26% 36
5001-10000 employees 64243 6.40% 13
1001-5000 employees 122687 12.23% 22
501-1000 employees 48677 3.09% 17
201-500 employees 43585 4.35% 13

Persona-driven Omnichannel Demand Gen Success

HIPB2B has successfully tested one omnichannel model – namely the use of email campaigns supplemented by LinkedIn B2B social media and ads – to give customers both leads and engagement data on an additive set of names that they can nurture or retarget.

A couple of items have been valid since our earliest days and still hold true:

  • Email is most often the primary channel in B2B demand gen.
  • Many companies use additional channels, but their tactics and customer views are siloed, meaning data from one channel doesn’t flow seamlessly to another to ensure the best customer experience.

These are the main reasons I think omnichannel marketing – whereby marketers use multiple channels, but the data flows from various channels into a central system IS seamless – has so much potential for demand gen. In our experience, omnichannel is primarily being used to drive awareness (and it has been quite successful).

Our testing process yielded a compelling use case for omnichannel demand gen: LinkedIn advertising that supplements lead-gen campaigns and delivers actionable engagement data within the filters our customers specify for their campaigns.

We leverage our customers’ campaign messaging in ads to drive those who engage with the ad to the same landing page as their email campaign while collecting advertising engagement data and additive form completions.

With LinkedIn ads, advertisers can build a target audience using demographic qualifiers or upload a list of their own with, for example, company domains and email addresses. We have used the latter approach because our database is a core business asset, but we expect most marketers will choose native LinkedIn targeting.

By advertising to LinkedIn members, our customers can reach a new audience with minimal overlap versus their email-generated leads; both sets of responders meet the campaign’s criteria such as company size, professional title, and industry.

LinkedIn advertising means our clients can secure a powerful blend of verified business card data and firmographics on leads, as well as data on those who engage with their ad. targeting, data capture, and prospect responses.

Coming Next

Stay tuned this December 14 as we wrap our blog series with the campaign surprise – BRAND 4 (HUMAN RESOURCES AUDIENCE).

You may also be interested in reading our recent eBook, Omnichannel Demand Gen 2021-2022.

On January 7, 2022, we’ll provide deeper intel on these four use case details regarding target audiences and ABM in our next eBook, “Omnichannel Demand Gen in Action.”

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