Sherry asks, "How do you use analytics to set marketing strategy, especially for social media marketing?"
While this is a very broad question, we can use our AI-Powered Social Media Marketing Process as the starting point for discussing the use of analytics in setting, informing, and executing strategy. Watch the video for a walkthrough.
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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.
In today's episode, Sherry asks, How do you use analytics to set marketing strategy, especially for social media marketing? This is a really broad question. But we can use analytics to inform, to set and to execute the strategies in marketing and and and social media, as long as we have a strategy or a plan or a framework to work from analytics is data and the analysis of what happened. And so if you're starting from net new then obviously going to have a real hard time creating something from essentially nothing right from just a bunch of data points. You can use it to you can use analytics to to build on on your strategy, but it's very hard to create a strategy from data itself in the same way that it's very hard to build a recipe just from ingredients, you should generally have the
The idea of what you want to make first and then see, okay, what ingredients do I have? Can I substitute things? The grandma told me some things out of the things definitely about critical. That's how you should approach this kind of question is what recipes? Do you know how to cook? And then do you have the ingredients necessary. So let's look at at one recipe. I'm going to bring this up here. This is the AI powered social media marketing processes is something that I do for trust and sites, customers, and something that that you can do as well, as long as you have access to the technology. And it is a 10 step process for using artificial intelligence, machine learning and data to build a really comprehensive marketing strategy around social media. So the first step when the the step, I think probably Sherry's alluded to most is that inventory step are we do have a good catalog of existing content, existing data, existing analytics and metrics, what do you have to do this is stuff that you have
in good condition, what does it tell you? What happened, what worked, what didn't work and so on and so forth. And that's the basis the starting point we in data sciences is called exploratory data analysis What do you have? Is it is it any good What does it tell you the next step is based on you identifying the things that worked you would then take for example if you're doing social media marketing and you isolate the top 10% of know Instagram posts in your industry enrich that extract out the the general content the topics too broad lists ideas to terms to phrases to keywords to images, two themes and figure out how to extend that so if the top 10% of Instagram posts you know 90% of those are like pictures of cats okay this is all cat so it's just house cats is a certain color cat. You want to get a broad idea after that you would use
artificial intelligence actually wouldn't even use it at this point. This point you'd be using
Research Tools to determine things like search volume. So things like Google Trends or sem rush or at our reps or spy food
to determine broad volumes that you use services like talk Walker and ran 24 and and all the media monitoring tools to help understand
what are the broad big discussion points and use those tools to determine the competitive landscape as well who's talking about these things? How are they talking about them from those you would you would select the things that you think you can credibly address so if you know nothing about cats, guess what you have to discard that 10 that top 10% of those cats posts and and you know about dogs, find the dog post, select them and then start to enrich that and this is where you would take all the social posts about dogs are all that were high performing, or all of the articles about coffee or SAS based software or server appliances or whatever the case may be and you would use
You would use media results. So articles, blog posts, Reddit posts, Facebook posts, you name it, and extract out a language model, a topic model of those things. So let's bring up an example here. This is from
a conference called shop talk, which is a retail conference. And we're running in an assessment of the right now. And what we can see in shop talks data is things like digital transformation, digital natives and things. These are these give us ideas and starting points to then go and do the opposite of that broadening. Now, we want to narrow down so we would take something like digital natives feed it into our SEO tool and get 5100 200 300 500,000
search terms related to that. The next step in the process is to use predictive analytics to forecast Okay, when will each of those thousand terms be at its most popular which ones are going to be popular on an ongoing basis?
What weeks of the year with those things
be powerful there's a example I'll put a link in the notes to our cheese OF THE WEEK forecast which uses a lot of this technology to innovate frivolous fun way to say like this is when the this the most popular cheese will be but use predictive analytics to guide your social calendar to guide your execution strategy to say this is when we're going to talk about these things we're going to create video content about digital natives we're going to create interviews about digital natives and we're going to have YouTube videos up about digital natives and we're going to time it so that when people search for digital natives the most and the next year our content is waiting for them they're they're ready for them
after that you like I said you build the content you constructed and then you have to go out and and from all those conversations you just had find your key opinion leaders your influencers based on those topics. So this is another example this is the the shop talk one and we use network graphic technology to figure out who are the people who are being talked about the most when
comes to this particular conference. Now, you would also do this for things like that your big topics like digital natives, or new age of retail, or whatever the thing is, but this is the distill phrase, the phase where you are identifying those people. And then if your content is good, then you do your outreach to those people at using the predictive calendar. So it's at the time that those people should be most interested in your topics.
So it's influencer marketing. But with instead of just kind of being scattershot and haphazard, using the data using your analytics to say this is when I should approach this person about this thing because this relevant to the industry and then you just repeat the cycle over and over again for each of the topics each of the areas of expertise, each domain knowledge area of domain knowledge that you have to do until you get the results that you want or or or you find out that maybe the area that you're creating.
content and doing outreach and isn't generating interest, right? So if you are
if you are a coffee shop and you're trying to reach out about coffee influences about your coffee shop, and it turns out that that may not be the reason people go to coffee shops, then you would have to switch over to doing pure market research and figure out why if we're reaching out about coffee and people like coffee, and we're a coffee shop and we've got coffee influencers. Why are we not getting results. Now, it could be your pitches bad, but assume it's not. It could turn out that people go to coffee shops for reasons other than the coffee Starbucks calls that third space, but whatever you call it, you have to do market research and then restart the cycle again, so that you can build new content, identify new influencers and so on and so forth. So that's a very cursory way to use the analytics and data that you have and build strategy from it. enrichment validation selection, extraction prediction construction Association
distillation and outreach as a process, it takes time and it takes some technology to do it. But if you do it well, you will, on average get much better results than someone just guessing and hoping to get lucky because you're using the data that customers and your audience are already creating and giving to you on a silver platter for your for your social media and content marketing strategy. As always, please subscribe to the YouTube channel and the newsletter and talk to you soon want help solving your company's data analytics and digital marketing problems. This is trust insights.ai today and let us know how we can help you
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