Do you create niche content? Do you know your customer journey? Have you ever thought of combining the two so that you’re creating niche content for the customer journey?
This got me thinking about content planning. In an ideal world, we could be everything to everyone. In the real world, we’re trying to reach our audience at a specific point in their customer journey when they need our content the most. This could be awareness, purchase, or every stage between. Thus demonstrating that you cannot be everything to everyone. Your awareness content won’t hit the same as the hard sell.
So - why can’t we do both? Why can’t we create niche content and mass appeal content?
You can. In my experience, companies that lean toward mass appeal content do so because they don’t have a great grasp of their customer journey. They don’t know the timing or the channels. It’s also easier to create mass appeal content (but that’s a topic for another time). What happens is they mismatch platforms and messaging and don’t provide specific information. It can be difficult to pinpoint when someone is at a specific stage of your customer journey if they are not live on your website.
I just had an interesting conversation with my friend Brooke Sellas from B Squared Media and she is working on this really cool measurement concept that tags social conversation for different customer journey stages. And it got me thinking - is this the solution I didn’t know I needed? Spoiler - the answer is yes.
When we (Trust Insights) do an attribution report we’re limited to understanding what comes into our website through different marketing channels. This is useful because we can make sure we’re reaching people at their appropriate customer journey stage and create content around that. The challenge is that perhaps the majority of our email subscriber list is at the engagement stage, but not everyone is. We don’t know that for certain with our reporting. So we throw in some language that sells our services. We make sure that we give context to who we are and what we do. We’re back to trying to be everything to everyone. And not everything happens on our website. To assume so would be incorrect.
And limiting yourself to only what happens on your site is reactive. I want to be more proactive and in the moment. I want to reach people before they even know we exist.
That’s where Brooke’s work is useful. She’s using social listening software and training the system to identify conversations around specific keywords and topics for different customer journey phases.
It blew my mind. It’s so simple, yet so genius.
What this does is allow companies to create that niche content for different audience segments and have it at the ready. Instead of broadcasting “This is what we do” on social media to everyone all the time, you can narrow down your focus and share that message with people who are ready to hear it. You’re not guessing. You’re cutting out the noise.
Like I said, mind blown.
This brings us to the “so what” this week. You should create broad and niche content. Broad content is for everyday use. It’s evergreen, it’s for anyone. Niche content is for select groups at select times. You need both in your arsenal. Start by figuring out what are the stages your customers go through on your sales funnel. Those are your customer journey phases. Then take a look at what they are doing in those phases. What do they typically engage with on your website? What kinds of questions do they ask? That will help you understand what they care about.
Think about it like this. If a prospect comes to you and says, “I’m interested in your blue widget, what are the technical requirements?” you want to have an FAQ ready. If all you have is a company overview, you’ve missed an opportunity. Don’t limit yourself to what happens on your website and don’t overlook the power of social listening.
In this week’s episode, Katie and Chris walk through what big data analytics are. What criteria separates regular data and big data? What are the four Vs of big data? How do big data analytics play a role in marketing analytics? Why don’t more marketers use big data and big data analytics to improve marketing? Tune in to find out!
Last week on So What? The Marketing Analytics and Insights Live show, we dug into the differences between Bing and Google when it comes to SEO. Catch the replay here »
Here’s some of our content from recent days that you might have missed. If you read something and enjoy it, please share it with a friend or colleague!
In this week’s Data Diaries, let’s tackle what could potentially be a controversial question: does website accessibility improve/affect SEO?
Why would this question be controversial? Because the answer could affect how some folks might approach their website optimization. If the answer is a flat out no, then accessibility might fall to the “nice to have” category on to-do lists.
To be clear, accessibility should never be on the “nice to have” lists because making a site accessible means appealing to more customers, period. For example, closed captions and subtitles aren’t just for folks with hearing impairments; they also make content more accessible for everyone including neurodivergent folks. If our websites are accessible to more people, it amplifies the impact of our marketing. According to the US CDC, approximately 10% of Americans have either a hearing or vision disability; if our sites lack accessibility, we automatically exclude potentially 10% of our future customers. You don’t need to be a data scientist to know that losing 10% of your customer base off the bat is a bad thing.
So, with that caveat out of the way, how would we determine whether accessibility impacts our SEO? We’d first need some objective way of measuring our SEO. Google Search Console data will do that for us; the number of times our site shows up in search is a good proxy for how relevant Google thinks we are. Part of that relevance is having a site that is easily crawled and indexed; accessibility features like alt tags on images, closed captions in video and audio, and use of W3C HTML standards all make accessibility software work well AND make our sites easier for Google’s crawlers to ingest.
Once we have a target outcome, we need to obtain accessibility data. Using IBM’s free Able Toolkit, we scanned the entire Trust Insights website and tallied up the number of identified errors per page, then merged that data with our Search Console data and data from the AHREFS SEO tool.
Let’s first look at a basic correlation:
What we see is a series of variables above the line of statistical significance such as referring domains, referring pages, backlinks, etc. - all known factors for what contributes to a site showing up in Google Search. Violations of accessibility guidelines is under the line of statistical significance in a simple correlation test. This doesn’t mean it has no impact, but any impact is has isn’t strong enough to be a very clear signal.
Let’s extend this analysis another step and use the machine learning library XGBoost to analyze our data and build a complex model for what drives impressions. Because of the way XGBoost’s models work, we can extract something called variable importance or feature importance. Without delving into the technical architecture of XGBoost, variable importance tells us what variables were used the most to construct an accurate model of our data. The more a variable is used, the more important and relevant it is to the outcome.
What we see above shows that violations of accessibility rules is the third most relevant variable in our model. While none of the variables are a “smoking gun” for what determines Google’s judgements about appearance in search, this isn’t a surprise. Google itself has said there are more than 200 different variables that go into the core search algorithm, many of which we do not have access to (such as user behavior). With the data we have, this is about as good an analysis as we can get.
What’s our takeaway here? Accessibility has to be part and parcel of our overall website optimization toolkit. Not only is it ethically and morally just good citizenship, it is also part and parcel of what we’re able to observe as influences to Google’s search algorithms.
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We heard you loud and clear. On Slack, in surveys, at events, you’ve said you want one thing more than anything else: Google Analytics 4 training.
What makes this different than other training courses?
You’ll learn how Google Tag Manager and Google Data Studio form the essential companion pieces to Google Analytics 4, and how to use them all together
You’ll learn how marketers specifically should use Google Analytics 4, including the new Explore Hub with real world applications and use cases
You’ll learn how to determine if a migration was done correctly, and especially what things are likely to go wrong
You’ll even learn how to hire (or be hired) for Google Analytics 4 talent specifically, not just general Google Analytics
And finally, you’ll learn how to rearrange Google Analytics 4’s menus to be a lot more sensible because that bothers everyone
With more than 5 hours of content across 17 lessons, plus templates, spreadsheets, transcripts, and certificates of completion, you’ll master Google Analytics 4 in ways no other course can teach you.
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Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.
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