When I last wrote of this in November, 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 serious outperformer, and even I was impressed.
But I would be remiss if I did not 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. 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 the “impressions intelligence” of the target audience.
The “surprise” performing audience – Human Resources
Here was a brand trying to reach human resources professionals, including recent new titles like talent acquisition, workplace wellness, and more. The brand itself is well known but thought of as a resource for the job seeker rather than the job offeror. To differentiate itself, the brand adopted a thought leadership-driven content strategy.
Their chosen approach was the unified use of two+ channels, concurrently running campaigns to the same audience. Here are the campaign basics, re the LinkedIn ad portion.
| BRAND 4 (HUMAN RESOURCES AUDIENCE) | |
|---|---|
| Report Start | August 2, 2021, 12:00 AM |
| Report End | August 31, 2021, 3:39 PM |
| Date Generated | August 31, 2021, 3:39 PM |
| Ad Budget | $913.66 |
| Campaign Duration | 30 days |
| Campaign Goal1 attained: 50+ clicks | 86 clicks |
| Campaign Goal2 attained | 500,000 impressions |
| Total impressions | 1,304,620 |
Again, 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 both ABM and persona-based targeting outcomes:
Company Name Segment |
Impressions |
% of Total Impressions |
|---|---|---|
| 7002 | 0.54% | |
| Actalent | 5180 | 0.40% |
| Robert Half | 3296 | 0.25% |
| Amazon | 3228 | 0.25% |
| Collabera Inc. | 2746 | 0.21% |
| TEKsystems | 2520 | 0.19% |
| Jobot | 2296 | 0.18% |
| Aerotek | 2108 | 0.16% |
| Northwestern Mutual | 2070 | 0.16% |
| NLB Services | 1980 | 0.15% |
| Artech LLC. | 1918 | 0.15% |
| Insight Global | 1804 | 0.14% |
| True Search | 1698 | 0.13% |
| Slalom | 1682 | 0.13% |
| US Tech Solutions | 1580 | 0.12% |
| Amazon Web Services (AWS) | 1570 | 0.12% |
| 1524 | 0.12% | |
| Deloitte | 1470 | 0.11% |
| LanceSoft, Inc. | 1468 | 0.11% |
| Michael Page | 1462 | 0.11% |
| Mindlance | 1462 | 0.11% |
| ByteDance | 1458 | 0.11% |
| Aston Carter | 1458 | 0.11% |
| PwC | 1380 | 0.11% |
Company Industry Segment |
Impressions |
% of Total Impressions |
Leads |
|---|---|---|---|
| Human Resources | 125230 | 9.60% | 43 |
| Staffing and Recruiting | 108534 | 8.32% | 19 |
| Information Technology and Services | 30262 | 2.32% | 16 |
| Computer Software | 55300 | 4.24% | 8 |
Company Size Segment |
Impressions |
% of Total Impressions |
Leads |
|---|---|---|---|
| 201-500 employees | 67642 | 5.19% | 10 |
| 501-1000 employees | 47608 | 3.65% | 10 |
| 1001-5000 employees | 149630 | 11.48% | 20 |
| 5001-10000 employees | 62570 | 4.80% | 12 |
| 10001+ employees | 206618 | 15.85% | 34 |
Using Geography and Other Filters to Identify Likely Prospects
It doesn’t often happen, though the analysis of this data will always “narrow the playing field.” But, in the case of this campaign to an HR audience, we were able to combine multiple data sets to identify the Chief People Officer of an enterprise software company.
First, we had the engagement data by company name/domain as shared above. Then, we had location segments down to urban regions. Lastly, we had both level and specific titles for the CXOs engaged.
Location Segment |
Impressions |
% of Total Impressions |
Leads |
|---|---|---|---|
| New York City Metropolitan Area | 178820 | 13.72% | 17 |
| San Francisco Bay Area | 81922 | 6.28% | 14 |
| Los Angeles Metropolitan Area | 69256 | 5.31% | 12 |
| Greater Chicago Area | 53608 | 4.11% | 9 |
| Greater Boston | 51492 | 3.95% | 8 |
| Washington DC-Baltimore Area | 42864 | 3.29% | 7 |
| Dallas-Fort Worth Metroplex | 36482 | 2.80% | 6 |
| Atlanta Metropolitan Area | 32784 | 2.52% | 6 |
| Greater Seattle Area | 28868 | 2.22% | 4 |
| Greater Houston | 27538 | 2.11% | 4 |
Job Seniority Segment |
Impressions |
% of Total Impressions |
Leads |
|---|---|---|---|
| Senior | 277288 | 21.27% | 18 |
| Manager | 110138 | 8.45% | 32 |
| Director | 73706 | 5.65% | 24 |
| VP | 26338 | 2.02% | 10 |
| CXO | 4292 | 0.33% | 2 |
The Campaign Results?
First off, with a goal of 50 leads driven from ads, attaining 86 leads was fantastic. And, of course, we executed a concurrent email campaign that resulted in 100 leads, all on its own.
The ROI on a marketing investment that was 50% higher than email-only was 186 leads and target group performance intelligence on over 1 million impressions. When applying our business model for monetizing omnichannel demand gen to this HR use case, we arrive at 400% of ad costs! But collecting data is just one step in an omnichannel campaign. Remember that infrastructure and UX are crucial, and unifying outcomes from diverse channels is paramount for omnichannel demand gen to be sustainable.
While we’ll have other blog posts more detailed around infrastructure and UX, I will touch on a couple of items here.
What infrastructure does it take to monetize omnichannel engagement?
Some B2B marketers build, maintain, and optimize their martech stack. Others look to third parties such as Integrate, whose cross-channel focus and robust marketing automation software effectively power omnichannel campaigns. Either way, your martech stack must be in place to make omnichannel demand gen a reality.
In total, 67% of marketers made a change last year. More than half of those who switch do so because of inadequate data centralization. Another 41% switch due to insufficient integration capabilities. And the highest percent of swapped systems represent the “core” of the martech stack, namely marketing automation, email distribution, and CRM systems.
Omnichannel has secured a prominent role in marketing campaigns aimed at awareness and thought leadership. Its core traits – cohesive UX and unified data in the martech stack – make it the compelling option for demand gen campaigns.
Omnichannel UX
To achieve optimal UX in omnichannel, you need a well-executed content marketing strategy featuring prominent brand marks driven by thought leadership. More on this in our blog post “Thought Leadership and Content Marketing as Strategic First, which is coming soon.
Coming up next
On January 7, 2022, we’ll provide much deeper intel on these four use case details in our next eBook, “Omnichannel Demand Gen in Action.”
