Especially when you’re asked to do more at the speed of light, your multi-channel strategy can easily end up not looking like a strategy at all.
That’s usually where the bigger question shows up: Are these channels actually working together, or are they being measured like separate programs?
That was the focus of Session 3 of SEJ Live, where I joined Shaun Bruno from CallRail to talk about how to build a multi-channel growth strategy that actually converts.
The full session is available to watch on demand here: SEJ Live On Demand.
During the session, we talked through how marketers can connect channels across the customer journey, where AI can help, and what still needs human judgment. We also covered attribution, creative workflows, and how to set expectations before a campaign launches.
This recap covers some of the main takeaways, while the full recording goes deeper into the channel playbooks and audience Q&A.
1. Give Each Channel A Clear Job
One of the biggest issues I see with multi-channel strategies is unclear expectations.
A business may have the right channels in place, but each one is being judged against the same goal. That usually means every campaign is expected to drive immediate conversions, regardless of where it sits in the customer journey.
The problem? That simply doesn’t reflect how people actually make decisions.
Someone might discover a brand through video, compare options through search, look for proof on social or Reddit, and convert later through email or branded search. As consumers, we do this all the time. We gather information in one place, validate it somewhere else, and take action when the timing or offer makes sense.
The challenge is that many teams still manage channels like separate programs.
Paid search and social have their own report. Email, organic, webinars, and video often get evaluated separately, too.
That setup makes it easy to ask which channel “won” the conversion. It makes it harder to understand how the channels worked together.
Before judging performance, marketers need to define the role of each channel.
Some channels are better at creating demand by introducing a problem or product category. Others are better at building trust by answering questions, addressing objections, or showing proof. Lower-funnel channels are usually stronger at capturing intent once someone is closer to making a decision.
Your goal at this step is to understand what each channel should contribute, then measure it against that role. Once that’s clear, the performance conversation becomes a lot more useful.
2. Measure Awareness By The Right Signals
Awareness is one of the easiest places for a multi-channel strategy to get misunderstood.
A brand says it needs more awareness, then ends up measuring those campaigns against bottom-funnel conversion goals. The marketer may be trying to build future demand, while the business is asking why the cost-per-acquisition does not look like branded search.
That gap needs to be addressed before the campaign launches.
If you are running YouTube, Meta, TikTok, CTV, audio, creator, or influencer campaigns, those channels may be reaching people who were not already looking for your brand. They can introduce the problem, build familiarity, and give people a reason to come back later.
Immediate CPA won’t show all of that.
For upper-funnel campaigns, I would look at signals such as branded search lift, returning visitors, direct traffic trends, video completion rates, first-party audience growth, assisted conversions, and downstream performance in other channels.
Those metrics can help show whether the campaign is creating more awareness and improving the path for other channels.
This is also where expectation-setting matters.
Before a campaign goes live, marketers should be clear about how it will be evaluated. That conversation may need to happen with leadership, finance, clients, or managers.
For example, if you’re launching a YouTube campaign, define what success looks like. Explain which metrics matter, which metrics are directional, and which metrics should not be used as the main decision point.
Without that alignment, upper-funnel campaigns are often the first to get cut. Then, a few months later, the same business may wonder why branded demand is not growing.
3. Use Mid-Funnel To Reduce Uncertainty
Mid-funnel is where a lot of brands start to lose people.
At this point, someone has already shown some level of interest. They may have watched a video, visited a product page, downloaded a guide, engaged with social content, or searched for comparison terms.
The next message should not be the same one that introduced them to the brand.
This is where the message needs to shift from problem awareness to proof and differentiation. If someone watched an awareness video, they may need more product education. If they visited a product page, they may need reviews, testimonials, or answers to common objections. If they downloaded a guide, they may need a clearer connection between the educational content and the solution.
The goal is to answer the questions that are keeping someone from moving forward.
Meta can support this with objection-focused creative, carousel ads, or video retargeting. Demand Gen and YouTube can help reinforce product education in a more visual format. LinkedIn can work well for case studies, business proof, and credibility in B2B. Email can help sequence the message once someone has shared their information.
I also think marketers should be careful about treating mid-funnel as only retargeting.
Retargeting can play a role, but mid-funnel can also include non-brand search, webinars, educational content, comparison pages, nurture sequences, and other touchpoints that help someone build confidence.
The question I like to ask is: What is preventing this person from taking the next step?
Maybe they don’t trust the brand yet. Maybe they don’t understand the difference between your product and another option. Maybe they need to see proof from someone who had the same problem.
Once you know what’s causing hesitation, the message sequencing becomes easier to build.
4. Keep Last-Click Attribution In Context
Lower-funnel campaigns often look like the best performers because they sit closest to the conversion.
Paid search, branded search, and retargeting tend to get the lead, the sale, and the credit. But in many cases, those channels are capturing demand that another channel helped create.
This is where last-click attribution can give an incomplete view of performance. It rewards the final touchpoint, even when earlier touchpoints played a meaningful role in the decision.
Last-click data can still be useful, especially for understanding which channels are driving immediate action. It just shouldn’t be the only way performance is evaluated.
In the session, Shaun talked about looking at attribution from multiple angles. That can include last click, balanced attribution models, total influence touchpoints, and view-through data for upper-funnel channels.
That type of reporting gives marketers more context when deciding where to invest.
A B2B company with a long sales cycle should not evaluate every channel the same way as a direct-to-consumer brand with a short buying window. The right approach depends on the business, the sales cycle, and the decisions the data needs to support.
Since attribution will never capture every touchpoint perfectly, the reporting should help marketers make better budget decisions with the data they do have.
Marketers still need to report numbers leadership can understand. Those numbers just need context, especially when channels are designed to play different roles.
5. Use AI To Improve Workflow
AI was a big part of the session because it is already changing how many marketing teams work.
For me, the more useful place to start is workflow. Where can AI reduce repetitive work, speed up analysis, or help the team get to a stronger starting point?
AI can help summarize reviews, organize customer research, cluster search queries, generate headline variations, build creative starting points, resize assets, flag anomalies, and pull themes from performance data.
Those use cases can save real time, especially for smaller teams.
AI doesn’t automatically know your positioning, margins, sales feedback, customer objections, compliance needs, or internal priorities. Those details have to be part of the process if you want the output to be useful.
That’s why I would look at the foundation before bringing AI into every part of the workflow.
- Is tracking clean?
- Are audiences clearly defined?
- Do you know the difference between the buyer, the user, and the influencer?
- Is the messaging clear?
- Do the landing pages answer the right questions?
- Does each channel have a defined role?
If those pieces are unclear, AI can help you move faster in the wrong direction. But, if those pieces are in place, AI can help the team move faster without handing over the strategy.
Build A Strategy That Can Adapt
Multi-channel growth gets a lot easier to evaluate when each channel has a clear role.
That doesn’t mean every path will be easy to measure. It also doesn’t mean every channel will show its value in the same report. But it does give marketers a more useful way to plan, test, and explain performance.
For me, that is where a lot of the work should happen next.
Look at the channels you are already using. Ask what each one is supposed to contribute. Then look at whether the message, campaign objective, landing page, and measurement approach support that role.
If the answer is unclear, adding another channel probably will not fix it.
AI can help improve parts of the workflow, especially around research, creative, reporting, and pattern recognition. But the strategy still needs human judgment. Marketers still need to define the customer, the message, the offer, and the signals that matter.
For anyone who wants the full discussion, including the channel playbooks, AI workflow examples, and audience Q&A, the complete session is available to watch on demand here: Watch SEJ Live On Demand.
SEJ Pro is also where the conversation continues beyond the live sessions. It gives marketers a place to ask follow-up questions, talk through what they are testing, and learn from experts and peers working through similar challenges.
A lot of teams are being asked to do more with less right now. Having a place to talk through what is working, what still feels unclear, and what deserves more testing can make those decisions feel a little less isolated.
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