{"id":14094,"date":"2020-11-11T12:16:32","date_gmt":"2020-11-11T06:46:32","guid":{"rendered":"https:\/\/www.karooya.com\/blog\/?p=14094"},"modified":"2020-11-11T12:16:34","modified_gmt":"2020-11-11T06:46:34","slug":"ppcchat-targeting-audience-assumptions-10th-november-2020","status":"publish","type":"post","link":"https:\/\/www.karooya.com\/blog\/ppcchat-targeting-audience-assumptions-10th-november-2020\/","title":{"rendered":"PPCChat | Targeting & Audience Assumptions | 10th November 2020"},"content":{"rendered":"\n

Julie F Bacchini<\/a> hosted this week’s PPCChat session where she asked experts view on Audience Targeting, Are they doing retargeting based on assumptions or facts, What is the worst audience assumption they had to deal with, and more.<\/p>\n\n\n\n\n\n\n\n

Q1: How do you use audience targeting in your PPC? On search? On social?<\/strong><\/h4>\n\n\n\n
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That’s kind of a big question. For social it’s about interests, behaviors, and lookalikes of app users & store visits. and sometimes I retarget from other platforms using utms. @JuliaVyse<\/a><\/p>\n\n\n\n

For search, it’s about keywords, and y’all know how I feel about HEAVY negative keywords. Then affinity\/in-market layered on, with a soupcon of retargeting off of YouTube viewers. @JuliaVyse<\/a><\/p>\n\n\n\n

In Search, mostly as Observation audiences with campaigns on automated bidding. In Social, they are the bread and the butter. @SEMFlem<\/a><\/p>\n\n\n\n

Audiences are bedrock for me. I’ve had to constantly revise my tactics as the targeting options change. It’s def not as simple as find the product, select “in-market” and profit. @armondhammer<\/a><\/p>\n\n\n\n

Audiences play a much bigger role on social. I use interest, custom, lookalikes (in their various forms on platforms). For search, audiences come in to play most frequently for retargeting. Always set audiences to observe and then incorporate if see something good. @NeptuneMoon<\/a><\/p>\n\n\n\n

Omnichannel can be really fun this way: like geofence your display campaigns around each billboard you buy. then retarget off the display viewers. get to ppl irl!! @JuliaVyse<\/a><\/p>\n\n\n\n

PPC is a LOT of audience observation before targeting. No assumptions, just data, until there is enough data for bid adjustments and finally targetting. @ynotweb<\/a><\/p>\n\n\n\n

Lately I’ve been using the “safety net” strategy from @PPCHartman<\/a> at MN Search Summit a lot recently. Here’s the original tweet: twitter.com\/timmhalloran\/s\u2026<\/a> I’ve been finding it a successful audience strategy for difficult industries with established players. @timmhalloran<\/a><\/p>\n\n\n\n

For search, it’s all about those keywords and having a solid negative keyword listen. For social, interest groups, LAL of past purchasers, FB\/IG engages etc. @adwordsgirl<\/a><\/p>\n\n\n\n

My biggest success has come from looking just upstream of my product and finding intent there. As well as custom audiences that combine some search with competitor site visits. @armondhammer<\/a><\/p>\n\n\n\n

I don’t really do social. For search, I treat keywords like mailing lists in direct mail. Audiences change the nature of those mailing lists, so I’ll treat those audiences very differently to how I treat “non-audiences.” @stevegibsonppc<\/a><\/p>\n\n\n\n

I duplicate adgroups\/campaigns and segment them by audience, so that I can control budget flow to more qualified vs less qualified groups. @JonKagan<\/a><\/p>\n\n\n\n

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Q2: How do you determine who should be part of the audiences you target? Does this differ on search or social?<\/strong><\/h4>\n\n\n\n
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Start with why, always. why would someone with this behaviour\/interest\/intent\/employment care about my product or service. why would they h8smash it? that’s your exclusion. @JuliaVyse<\/a><\/p>\n\n\n\n

I do a lot of narrow targeting, esp B2B. If they follow an industry group, they’re prime, for one example. It’s so important to go beyond just what you do and get into what your customer does with the other 23.99 hours of their day. @armondhammer<\/a><\/p>\n\n\n\n

I start with what the client brings to the table (the more data the better…) and then do my own digging into historical data and competitive landscape. Look for blindspots or underperforming demos. This applies more heavily to social. @NeptuneMoon<\/a><\/p>\n\n\n\n

A lot of black magic and behavioral analysis. @JonKagan<\/a><\/p>\n\n\n\n

When you find underperforming demos, I want to know *could* they perform better or are they just not the right fit? This is important to figure out! @NeptuneMoon<\/a><\/p>\n\n\n\n

We start with asking our client who they think their audience is and then get as much info from the data they have to confirm their notion. We start a bit wider w targeting then narrow down. @adwordsgirl<\/a><\/p>\n\n\n\n

Exclusions can be massive, but dangerous. Pull out “in college” and you might eliminate the person that’s a performer doing a nighttime MBA class. @armondhammer<\/a><\/p>\n\n\n\n

For search, definitely past visitors. Then I’ll play around with different lists as an observation. And, whichever lists are producing interesting results, I’ll go deeper with. @stevegibsonppc<\/a><\/p>\n\n\n\n

My main use case lately has been 2 clients who sell products where they want B2B, but searches skew B2C – like lighting. It’s helped to be able to add audiences like “Business Services” to the mix. @SEMFlem<\/a><\/p>\n\n\n\n

My gut response was that “it depends on what levers I’m given” but I find that I’m discovering new audience tactics all the time that I hadn’t thought of, even though I had them at my disposal. I was told something this morning about Lookalikes that I never knew. \/1 @timmhalloran<\/a><\/p>\n\n\n\n

Also, I think there’s going to be a lot of innovation this year with server-side cookies become more commonplace. I’m kinda excited to see how things shape up. \/2 @timmhalloran<\/a><\/p>\n\n\n\n

Research is super important, but you also need lots of sources. We definitely need what the client has, but also what biases they might bring with it. 1st party must be used in conjunction with ComScore, surveys, and of course, behavioural. @JuliaVyse<\/a><\/p>\n\n\n\n

Using GA, and channels’ analysis if it exists to see if we can generate any lookalikes. For sure the customer match LAL are one of the most important and impactful, so getting with the client to see what they have. @360vardi<\/a><\/p>\n\n\n\n

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Q3: Do you develop demographic profiles or personas based on customer data? If so, how do you do this?<\/strong><\/h4>\n\n\n\n
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Con’t – look at that data. see what people are looking at while your ads play. are they looking at makeup? are they streaming an online game? these are very useful interests to apply to other platforms. @JuliaVyse<\/a><\/p>\n\n\n\n

I try to get my hands on as much customer data as they can give me. I find that clients often have wonky views on who their actual customers are – at least they don’t know that they have certain significant sets that are not what they’d say if you asked. @NeptuneMoon<\/a><\/p>\n\n\n\n

Yes. but we do it off 3 sources, and run them in case they differ. Data from CRM, GA (website), and who the brand thinks is the right customer. @JonKagan<\/a><\/p>\n\n\n\n

I then cross check their SALES and LEAD data with the demographic info I can get from platforms, GA, etc. Then map it all out – what assumptions are spot on and which are totally unknown? Start working on more nuanced efforts. @NeptuneMoon<\/a><\/p>\n\n\n\n

The same is true with your Twitter campaigns. you’ll see your interests and the results, but also your Also Reached. there’s good data in there!!! @JuliaVyse<\/a><\/p>\n\n\n\n

I think it’s important for Lead gen to get not all the customer match leads to create LAL, but the qualified leads. We saw that cleans up things. Garbage in. garbage out. @360vardi<\/a><\/p>\n\n\n\n

Usually a combination of 3-4 sources — current customer segments (CRM data), Web Analytics data (GA\/Adobe), Customer Insights (surveys and\/or focus groups) and people’s ideas (usually the least reliable). Collect + build into personas, which are constantly updated. @DigitalSamIAm<\/a><\/p>\n\n\n\n

I mostly follow the lead of the client. I may make suggestions based on them not knowing available audiences and different demos, but I have to rely on them to know their audience. After that, let the data do the talking. @SEMFlem<\/a><\/p>\n\n\n\n

The linkedin insight tag and The audience insights part of google ads can be a treasure trove. @armondhammer<\/a><\/p>\n\n\n\n

I guess I see the bulk of my role educating the client on what’s possible. For example, most of them will have no idea that you can choose different company sizes on LI. @SEMFlem<\/a><\/p>\n\n\n\n

I pull it from a few areas. Hopefully you can get some good demographic data from customers via Google Analytics, Ads etc. – but developing personas comes from testing audiences I’ve found and tested in social. @RyBen3<\/a><\/p>\n\n\n\n

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Q4: Do you have ways that you verify that your assumptions about your audiences are correct? Does this vary by search or social?<\/strong><\/h4>\n\n\n\n
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We look at performance and ppost-campaign surveys to validate hypotheses. @JuliaVyse<\/a><\/p>\n\n\n\n

“Suck it and see.” (For search.) Though, if I were doing social, you’ve got to start with some assumptions. You can’t advertise to everybody. (Usually.) @stevegibsonppc<\/a><\/p>\n\n\n\n

If it performs well, then it is right #ILoveAssumingStuff<\/a> @JonKagan<\/a><\/p>\n\n\n\n

I always look below the surface to see if there are golden data points just waiting to be discovered! Again, cross checking who is interacting w\/ the ads against targeted characteristics. And then who buys\/converts in the same way. Then TEST like crazy. @NeptuneMoon<\/a><\/p>\n\n\n\n

I feel like that’s why i’m in this business because of the instant validation\/gratification that comes from the audience converting. I think it’s a long term play. If the audience is continuing to convert for months, it’s a prime audience for you. @RyBen3<\/a><\/p>\n\n\n\n

I trust more social insights than search and audiences in social are more important for us to get right. @360vardi<\/a><\/p>\n\n\n\n

Going back to my personal example, asking questions about things we might have missed in the original targeting that is being revealed in who converts. Looking for subsets that might explain and seeing if they make sense to target more substantially. @NeptuneMoon<\/a><\/p>\n\n\n\n

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Q5: If you are doing retargeting, is it based on the assumption that people who did not complete the desired action simply got interrupted? Or does it allow for the fact that some might just \u201cchoose another option\u201d?<\/strong><\/h4>\n\n\n\n
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Qualify them. Don’t retarget everyone who visits your homepage (unless your pool is super small). Target those who land a few layers deep. Whether that’s category or PDP or for B2B that could be landing on an actual lead form, find people that are taking action. @RyBen3<\/a><\/p>\n\n\n\n

I love the “choose your own adventure” type of retargeting. Start broad and let them self select what the next action is based upon what they click. Nothing better than the data a prospect tells you themselves. @armondhammer<\/a><\/p>\n\n\n\n

(sorry for the pause\/interruption). Retargetting is based on the common knowledge that it takes multiple touches to close a sale. People look, look again, check their options, come back again… 7-13 times on average, especially with expensive products\/services. @ynotweb<\/a><\/p>\n\n\n\n

Depends on the product for us. For my restaurant client, retargeting is about returning and purchasing again. My public sector clients are all about changing behaviour = lots of reminders. My B2B clients need a long time to decide. different per audience. @JuliaVyse<\/a><\/p>\n\n\n\n

I always prefer to have a tiered retargeting effort, with the most resources going to those who are more likely, or showing more signs of likeliness, of converting. I’m amazed at the number of “one size fits all” retargeting approaches I see! @NeptuneMoon<\/a><\/p>\n\n\n\n

I’ve written 90% of a blog post where I look at this from a unique angle. It depends on the business model & where they quit in the funnel. (And the likely reasons why they quit.) @stevegibsonppc<\/a><\/p>\n\n\n\n

One of the issues with retargeting is that it shows such massive ROI (on a last click basis) that it seems like it’s a trivial expense Nespresso would be better served convincing me to tweet about their product rather than blindly showing me what I just bought. @armondhammer<\/a><\/p>\n\n\n\n

I think you need to allow for both possibilities; frequency capping on initial (general) campaigns, plus some sequencing, can usually weed out the nonviable\/noninterested prospects pretty efficiently. @DigitalSamIAm<\/a><\/p>\n\n\n\n

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Q6: Do you have an example of a time when you made an audience or demographic discovery that really surprised you?<\/strong><\/h4>\n\n\n\n
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Not surprising to me, but ultra-important to the client. Higher-ed client was recently targeting the whole US (on purpose) while 61% of enrollees lived within 30 miles of campus. @SEMFlem<\/a><\/p>\n\n\n\n

A bunch! lots of weird little pockets of high performance geos that don’t necessarily match the audience demo. Work from home has changed a lot of the landscape! @JuliaVyse<\/a><\/p>\n\n\n\n

I had a client years ago that was in the construction industry. They thought their best customers were school districts, turns out it was churches. Plumbing\/HVAC client swore they served ALL of 4 counties. Nah, it was mostly within 10 miles of their offices. @NeptuneMoon<\/a><\/p>\n\n\n\n

Lots. “In-market” audiences converting worse than the general audience; the time we learned one age group made purchase decisions in an industry predominantly owned by another age-group, and visitors to competitor sites were the worst performing audience in another. @ynotweb<\/a><\/p>\n\n\n\n

I recently found an audience just by reading through customers reviews. We tested about 2-3 of them and one has been a rockstar prospecting campaign. Always be testing! @RyBen3<\/a><\/p>\n\n\n\n

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Q7: What was the worst audience assumption you\u2019ve had to deal with? How\/did you overcome it?<\/strong><\/h4>\n\n\n\n
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I had an smb client who was utterly convinced that former\/retired law enforcement was THE thing for their business. it wasn’t, it was just high performing ad copy. The audience was not related to law enforcement or any particular prior career. @JuliaVyse<\/a><\/p>\n\n\n\n

The worst is often the search terms that clients think are used. A telecom client might type 5G, but so will a lot of other people for very different reasons. @armondhammer<\/a><\/p>\n\n\n\n

Consistently when the client thinks highest income earners are their client base, when it’s something like top 30-50% only. @ynotweb<\/a><\/p>\n\n\n\n

I think there is often a top X% bias in what\/who clients think to buy their stuff – be it household income, education level, job title level (there are a lot more people outside the C Suite than in it that buy stuff!). Data usually helps change ideas on audiences. @NeptuneMoon<\/a><\/p>\n\n\n\n

“Everyone is our customer”. Not true. You waste a lot of ad spend trying to reach everyone. The counter\u2013However, if you have a ton of pixel data, you can target BROAD and let the algorithms find the people most likely to buy. Those are two different arguments. @RyBen3<\/a><\/p>\n\n\n\n

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PPCChat Participants<\/strong><\/p>\n\n\n\n