Camp CallRail Workshop, Creating Campaigns. Session 3: Rachel Ward, Demand Gen Marketing Manager at CallRail, Katie Glaisyer, Media Director at Merlino Media Group, and Madison Roberts and Nick Lange of LumenAd run through how you can create data driven campaign strategies.
Rachel: My name is Rachel Ward. I work for CallRail, as a Demand Gen Marketing Manager. I work specifically on our customer marketing side. Something interesting about myself or something different is, I spent 13 years in the adult beverage industry before switching over to digital marketing in the SAS industry.
Katie: Hi, I'm Katie Glaisyer, Media Director at Merlino Media Group, so we do all things paid media. We have clients that are regionally focused, fairly small to medium sized businesses that we focus with neighborhood nuance, community nuance, all the way to large national accounts with a singular focus.
Nick: Hey guys, my name's Nick Lange. I am the Director of Omnichannel Solutions at LumenAD. I focus on the technical side of media buying, whether it's through the different ad buying platforms, working with CallRail and their solutions and tying everything together, and managing our product offering. LumenAD is an advertising intelligence platform that helps marketers understand how to best invest their next ad dollar.
Madison: Hello, everyone. My name's Madison Roberts. I am the Director of Media Services at LumenAD. I've been with LumenAD for about a year now. I worked at Amazon advertising prior to this for several years, which got me a lot of experience in the creative, analytical planning and operations side of the industry. Have joined forces with LumenAD for more of the advertising intelligence side of it.
- Leveraging campaign data
- Aligning digital strategy with advertising investments
- Leveraging CallRail data
Leveraging your campaign data
Madison: Let's spend some time discussing how to leverage your campaign data most effectively, and what makes up the essential needs of a data strategy.
Advertising suffers from TMI
We as marketers have more data at our fingertips than we've ever had before, yet the insights we continue to receive remain superficial and the times incomplete. Glaring statistic is that 74% of marketers question the quality and accuracy of their data. In an industry where we rely heavily on these metrics to make informed, strategic business decisions on behalf of ourselves and our customers, it's concerning.
We commonly see several layers of marketing tech being applied to a single campaign tactic, that's intended to offer marketers more value and more insights. While that may be true, the problem still remains that at this point it's still just a lot of information for you to sift through. That siloed information then leads to more questions than it does answers, which is the exact opposite of what your campaign data should be doing for you.
The challenge for marketers here is their ability to demonstrate the impact advertising has on their business. The amount of information accessible to marketers is overwhelming and it hinders their ability to manage data and glean insights. Therefore, our ability to iterate on campaign performance to achieve the most optimal results.
This is why as marketers, we shouldn't put off organizing campaign data until it's time for reporting. The time to do that is during your media planning stages. So before you invest a single ad dollar, your entire team needs to understand how your media plan translates into clear data outputs. This step helps prevent confusion about how a particular outcome is being achieved. It allows for more efficient optimizations, and streamlines communications with all internal stakeholders. Plus, it just builds trust throughout the entire planning and execution process, whether that's with your partner or a team member involved.
Challenges for marketers
- Customer churn
- Low profitability
- Growth is elusive
Marketers need to include a blueprint or a data strategy for unifying their advertising tech stack to consistently demonstrate the impact of every ad dollar. While there are many components that make up your data strategy or a successful strategy that you're putting together, I'm going to spend some time on three specific essential areas today: A singular definition of success Aligning and prioritizing campaign strategy with your reporting needs Data hierarchy and nomenclature.
What is a singular definition of success?
The common pitfall is to group too many indicators of success into one campaign. There is a difference between a KPI and a leading indicator. A strong partner knows them and separates these expectations from the get go before your campaign launches. So, how are these different, and why should you care? Key performance indicators are the critical measurable component of progress towards an intended result. This is the team's focus for strategic and operational improvements that help lead an analytical basis for business impacting decision making.
In the advertising world, this condenses this into measurable metrics that a team can optimize towards:
- Customer acquisition cost (CAC)
- Cost for acquisition
- Sales target
- New profit margin percentages
- Return on assets or investments
The leading indicator is input oriented, so they're often times hard to measure, easy to influence, and you can't directly or easily impact the business decision when looking at the results in isolation. It determines what measures you need to be taking to predict the intended outcome. If you can't decide on a single KPI, you should be reallocating that budget into a separate campaign effort so you have your tactics clearly defined, the success measurements to achieve that objective.
The answer should not be trying to fit all of these pieces into one campaign tactic. You will get confused by the results and the team will be split trying to accomplish several different areas of success for one goal. It's not strategic, and then in terms just stretches your advertising dollars too thin.
Ensuring all facets of the advertising lifecycle are aligned around the KPI is critical to campaign success. From the campaign brief to the final report, it's important that marketers unify workflows and technology partners with a clear definition to avoid confusion about how success is being quantified to the end client.
Prioritizing and identifying data needs
Translating a campaign strategy into reporting needs upfront. How you expect to review performance, eliminate surprises at what to expect during reporting, or maybe your quarterly review periods, and it ensures you account for measuring the most important components of campaign outputs, while also allowing you to confirm that what you're looking for in a report is in fact, measureable. Coming back to the leading indicator versus KPI conversation.
Data hierarchy and nomenclature
How can something so simple as data hierarchy bring so much accountability to media strategy? The questions marketers should be asking during their media planning stages, this is a couple of summaries or a couple scenarios of some questions, is:
- What targeting options are available for reaching my audience?
- What message will achieve my desired outcome or action?
- What is my desired business outcome?
- What tactics are needed to support the objective?
- What am I identifying as a business?
By outlining a data visual, it organizes your data outputs from different platforms into a common nomenclature. The glossary of sorts across platforms that can centralize all of your digital and traditional media efforts into one normalized software and business reporting tool, which is where a company as LumenAD comes into play. Finding that missing piece to that hierarchy puzzle, which is the advertising intelligence. You need to be able to go back to your data hierarchy and while one channel may be performing better, you want to be able to understand success at each tactic and be able to reallocate and shift strategy accordingly and in real time.
My recommendation to the audience here is to answer these questions when you're building out a data strategy, and identifying a home for every data source:
- How does your data hierarchy bring accountability to the impact of your media investments?
- How are you organizing that data output from different platforms into a common nomenclature, naming conventions, glossary of terms?
- How can you ensure that ad buying platforms with different data languages are coming together smoothly?
Then, align your strategy with how you expect to receive results at every tactic level of your campaign. Then your data is outlined and easily rolls up into one centralized report so that you in turn as marketers can easily retrieve those insights and optimize accordingly. This is how you can best leverage your campaign data most effectively, while bringing accountability to the business results and data accuracy. Start at reporting your data hierarchy, and work backwards into your strategy. Take the time to do that right, and that will all align with your campaign and business objectives.
Aligning digital strategy with advertising investments
Katie: There's three main areas that when we take this into the execution phase, that you need to keep into consideration, to really tie back into that total data strategy. So, the three main phases there to execution would be:
- Campaign briefing
- Buy structure
- Analysis and communication
This is not only briefing with your clients, that's very, very important, but once you have established agreement on that brief, really making sure that any partner or vendor that you're working with understands every stage even if they don't plug into every single stage of that. So that we all know what we're working towards and we're all rolling in the same direction, obviously.
The one thing that I think is really critical in the briefing phase, is not only really discussing with the client what part of the funnel that we're going to focus on, or the whole funnel that we're going to focus on, but what channels that we'll utilize in each phase of that campaign. Additionally, the messaging that goes along with that. As we all know, that first touch versus a retouch is probably a little different from the communication phase, as well as the channel selection phase. Really ensuring that that all marries together and that everybody is agreement on what that should be.
I've got an example here of, I know that this seems really basic, but believe it or not, we get tripped up in the briefing phase all the time. I have a client recently that they had quite a bit of research conducted. They just weren't gaining traction like they wanted to. The research came back and said that they didn't have credibility with their audience, and they were lacking in quite a bit of brand awareness. It was all agreed upon by all parties that we were going to focus on the upper funnel portion of that customer journey. What that means from a KPI standpoint are things like engagement and reach, but necessarily optimizing towards that cost per conversion necessarily. So, as an agency, sometimes we take this for granted, that clients understand that if that's our KPI, that's what we're working towards, and that we're going to do that for a period of time to really gain that credibility.
We went live with the campaign and within two weeks, I had my client looking at cost per conversions, and some business level data for actual transactional counts and locations. I really had to have them take a step back and say, "Hey, we all agreed to work on this upper funnel."
The other thing that's really important is if a client does agree to an upper funnel KPI, the gold standard would be to have some pre and post research out in the marketplace that shows that we are moving credibility with our consumer, and that we are gaining awareness. If the client is unable to purchase that kind of research, that they're very, very clear on what the output is going to be in the data and what we're working towards in the near term.
The next portion that I think is really critical too, is making sure that you have that set up so that you can report back on that data strategy. This is very, very critical. I had a client recently also come to me and they said, "Katie, this year, this is all about reacting at the center level." They had 50 different centers, and they wanted to be able to react, sometimes on a monthly basis to shift things around to really ensure that they were meeting overall business objectives as a whole. They knew that the way to do that was to shift dollars by location based on the volume that they had available there, or if they had an operational issue at a location, maybe we needed to pull back. In previous years, we weren't necessarily as agile in making those shifts in real time.
The first thing that we did, we actually had some offline tactics that were working for them in upper funnel, which worked really great for them but it doesn't allow us to be as agile as we needed to be for that particular year and what our objectives were. Shifting to a completely online strategy that allowed us to do that while utilizing channels, there's still upper funnel channels that we could utilize in the digital space, but then ensuring that we can make those changes as needed.
Instead of setting up our ad buy at the channel level and then the center level, it became very, very clear that the hierarchy there needed to be the center level, and then the channels underneath that, so that we could in real time make shifts to insertion orders and ensure that we were delivering changes to the client at the speed that they needed them to be done.
Analysis and communication
This is also obviously a very critical stage of the process. The thing that I really like as an agency about using the LumenAD platform, is it allows me to marry those media level media results, along with the business level results that then my clients are looking at, so that we can not only in real time see that media and channel performance, but I can ingest my client's business level data and see what's happening at a center level there.
A lot of times when we have data at our fingertips, we want to make changes very quickly. I find myself oftentimes trying to remind clients that we really need to make sure that we have data at scale to ensure that there's a pattern emerging here that we think is really emerging.
While we will obviously make channel changes and media changes on a daily basis, I really encourage clients to, let's watch the business trend for a couple, three weeks. Make sure we've got some scale there and some impressions there, to validate the results that we're really seeing. So, that's one note of caution with that data at your fingertips.
Leveraging CallRail data
Nick: In this next section, Rachel and I are going to go over how to implement, leverage, and utilize CallRail data, some of those best practices that we use here at LumenAD and at CallRail.
Key variables: How to determine how many phone numbers your ad campaign needs
It's a great question because there isn't a one size fits all answer. It's not affixed, it's totally subject to your data hierarchy or how your campaign is structured.
What we like to look at is, we assign one number to a given tactic. To define a tactic, a tactic is a specific technique, action, or tool that's used to achieve a strategy supportive of your overall objectives. But most importantly, it's equivalent to a campaign and an ad buying platform.
A couple of examples of a tactics:
- Channel: you could just be running a Facebook or display campaign.
- Channel plus a strategy
- Channel plus market, and a channel plus market or strategy
For example, for this campaign here, we're looking at a campaign that's utilizing three different channels across 10 different markets. So in this, because we're doing three channels across 10 markets, that will be 30 different tactics. We'll want to assign 30 different numbers, so it's a one to one ratio within each tactic.
Once we have our numbers, we need to implement them. The way we do that at LumenAD, is we use dynamic phone numbers. What a dynamic phone number is, is a phone number that's actively swapping on a landing page, depending on what key variables we put in place. The key variables that we put in place come from the UTM structure.
When that UTM goes through, we'll utilize that UTM's string on the atlanta display tactic. At scale, this is what our campaign or a little glimpse of what the different UTMs we'd be utilizing for the campaign that I showed earlier.
Once we have that UTM structure in place and implemented on the ad buying platforms, we need to do something on the back end on the landing page view to make sure we're swapping the CallRail number with the original number.
We wrote a script that analyzes when a user comes to the page, it picks up the page path. It scans the UTMs to look for these different variables that land a display. Then it'll scan through the actual landing page looking for that original phone number and swapping it with the correct CallRail number that we set up for this given tactic.
Take a step back and just go through what that user journey looks like:
- User surfs through Facebook and sees a Facebook ad.
- User clicks on it (it’s a gym sign-up)
- They go through to the landing page with that UTM structure that we have assigned for that tactic.
So the UTM campaign would be LA 2020 conversion Missoula (that’s their location). The source would be Facebook. Then on the back end that script is running, and it finds those UTMs that we have on my user level, and swaps it with the correct Missoula Facebook number. Therefore, we're able to attribute calls to the different specific tactics and optimize accordingly.
The last piece to this puzzle is tying all this information together. We have three different ad buying platforms. We have CallRail reporting on our CallRail conversions. We could get into spreadsheet mayhem very quickly in order to understand what's going on. That's how you utilize LumenAD and LumenAD's software. We have different API integrations with all these different ad buying platforms, but ingest your data into one place and you can analyze all this data within one screen all 30 tactics, looking at your CallRail data, your impression level data, your click data. You can easily see what your cost per calls are. That allows marketers to make impactful decisions on their campaigns quickly.
Rachel: Nick was talking about one to one tracking, which is also called our source tracking, but we do have other options and if you're driving someone to the website, you could use a keyword pull, and we call this our keyword level tracking.
Essentially, going back to Nick's example of Nick. The user clicks on a Facebook ad and it lands on the website. Now, you have a keyword pull set up and so you can understand in CallRail platform, it assigns a specific number to that website visitor. So you will know a lot more information, a lot more granular data, which can also help inform your strategies if you need to pivot, or for future campaigns when you're looking at how something performed.
The user goes to the website and he visits three different pages about five to 10 seconds per page. They make a call or fill out a form on your pricing page. So, all of that information is now in CallRail. You can see the information, the keywords that got them there if it's Facebook, maybe it won't be that he landed on Facebook from a Google keyword search, but maybe it is. But we give you a lot more information.
Then to take that a step further where our keyword pull, which we call it keyword level tracking because we are pulling in keyword search information, you can take it a step further with keyword spotting. Maybe you know that your Google ad is driving the majority of your calls, but if you set up keyword spotting, which can help you qualify your call or tag your calls as qualified, where your calls are recorded or your forms are also brought it.
You can look at call-in forms, specific keywords, and then it will tag them or qualify them automatically. So now, you can even dive deeper and learn, okay which keywords are bringing in the most qualified calls, or which ads are bringing in the most qualified calls? Because maybe you're getting the highest call volume out of Google Ads, but your Facebook has a much higher conversion rate, much higher quality.
Then call highlights is something that also goes along with, takes keyword spotting a step further, where SEO really likes this but also, if you're looking for new keywords, call highlights will start to recognize trends in your calls and recognize keywords that are continuously coming up. It will surface that for you and it will give you meaningful insights into your business to let you know, maybe you aren't looking for it and you hadn't considered it. In turn, it can also let you know that if you have an ad in your content, maybe isn't quite speaking well to the right client and you have the wrong people calling in or the wrong people coming in. Let's say you're a dentist's office and people are coming in and filling out an appointment form online, and they think that they're seeing a general practitioner. That might be a bit of a stretch, but you get the point, it can help you surface things that are working but also that aren't working.
1. What's the best way to deal with spam or bot calls? As user of CallRail, do you have any best practices that you like to utilize to deal with these calls?
Nick: It's dependent on typically the brand. We see some more than others. Typically, we'll look at the phone calls and look at the phone call durations. The CallRail data makes it pretty easy to pick up what's spam and what's not. We'll just filter those out. It can be a manual process and typically like I said, it's specific to the brand you're utilizing or advertising for.
2. How do you segment your customers?
Katie: It's so dependent by vertical and brand. I don't know, I'm working on a piece of business right now where the focus is on growth customer, doing a ton of segmentation with different growth segments, versus bulking in that core. I think the first is just identifying through purchase data, what those segments are. Then if there is a lacking, like the client that I'm working on currently, we think that there's some potential with an audience that's not currently a customer. Focus on really building that out significantly. We can collect website data, but not always are we getting a growth customer through the website, so that's not always the best way to segment. But really, looking at... I mean, this particular client's a retailer, so looking at that particular product and where people buy it in other places.
Rachel: Yeah, I think so there was a little bit more insight given. So, how do you segment your customers within CallRail, where buy customers call in and get tagged? So, I know from my end I can answer that. We do have a list of common tags used per industry that we can always provide for you if that would help you get a starting point if you're looking at how you want to tag your calls and maybe what are some best practices around that.
Katie: Yeah, it does. The client that I'm specifically mostly using CallRail for right now is a healthcare client. We tag them and segment them by services that are needed. We have all of the appointment level data on the back end that we can tie to the CallRail data.
Rachel: Awesome, and I mean tags you can get very down and dirty with. You can tag per campaign specifically, per type of customer or industry. Let's see, and, can customer's CSV list of phone numbers live as a bucket inside CallRail and get recognized when calls come in? Can customers? Can you load your client's first party data and then it can be recognized as a current customer?
Katie: That's actually a great question because as marketers and especially as the agency, we're tasked with new business versus repeat all the time, but yeah. So it is good to be able to segment in that way, what's new and what's repeat.
Catch the next Camp CallRail session:
- Storytelling: Creating Content that Converts
- Treasure Hunt: Mapping the buyer journey all the way to conversion
- Arts and Crafts: Creating Campaigns that Close
- Archery: Targeting Repeat Customers
- Buddy Check: Identifying Revenue-Driving Partners