AI for success – the Digital Marketer
Data and AI help to make money for a business by showing what’s going on, and then explaining what to do next.
Google Maps is a good example. Google uses its data to show you the journey ahead plus the time it’s likely to take. But if a delay happens, Google will use AI to figure out the best alternative route to take.
Can a business build this sort of capability for themselves? Increasingly so, and this series of blogs about businesses putting AI to work describe what’s possible.
Abi the Digital Marketer
To grow her digital marketing agency there are two things Abi wanted to be a whole lot better at:
Getting social media post content right by quickly discovering what works and what doesn’t.
Setting up a campaign using all the main social media platforms, plus email, to maximise the hits on her client’s website.
And, if she’s to make a profit, achieve both within the period of time budgeted for the client.
Abi’s social media management platform helped. Although she had to use trial and error to get content right, she could edit everything (except for emails), and see the response to all her posts, all in one place.
As each campaign grew, the platform could give her all the data she wanted about engagement, the audience, and the effect her content was having – including a record of website hits, captured through Google Analytics.
Which meant she had metrics – a whole raft of them – impressions, likes, hashtags, comments, messages, audience growth, top posts, video performance, demographics.
However, even though this list included everything it was possible to collect, Abi still couldn’t answer a fundamental question:
What combination of emails and posts, across all the different platforms, will give the greatest number of hits on a client’s website – given the time budget involved?
For this she needed to take her use of data on one step further, and bring AI into play.
This involved building a specific set of data from all the records she could collect. It included each hit on the website, along with key features from every post and email that could be linked to each hit – where features ranged from times of messages and choice of platform through to the themes and images reflected in the content.
An AI algorithm then used the patterns and relationships in the data to show which features did most to explain the website hits received.
Abi could use this explanation to predict the website hits she could then expect for any pattern of social media and email activity she chose. She could also find the pattern of activity that should yield the maximum number of hits for the time involved.
How does she make money from this?
Abi still allocates the same amount of time in her day to each client. But she now gets more hits on her client’s website than before, which boosts her reputation, and her clients keep coming back for more.
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Achieving success through AI and data.
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