The most important part in marketing is making sure that you are up to date and have relevant fresh content out there for your target audience to read. Studies have shown that when looking to make a purchase, 61% of customers made their decisions based on the recommendations they read on a blog. This is why automated content creation tools have become very popular. These are tools that use new technology such as natural language generation to produce written content in a very short space of time. Two in every three marketers today are using automated tools in their campaigns because they help to generate more traffic as well as push out more content for a larger audience to see. Algorithms are the most common form of automated content creation. For example, Social Bakers is a popular tool that generates content for social media marketing. It uses NLP or Natural Language Processing which is a form of AI to turn data and complex reports into content written in simple human language. This can be in the form of something like a social media post which you can schedule to be put out on sites such as Facebook and Instagram. It also has the capacity to produce content for longer articles and blogs. Such as the blog here on Impressona. The beauty of using this tool is that you can tailor content to suit your individual customers and audience. By researching and finding what keywords and search terms they are using to look for your products or services, you can put that into the tool and it will create content that includes those words and phrases. This will help to boost your search engine optimisation, making your website more visible when people search using those keywords. Another advantage is that using such technology means that less time is wasted on producing content manually and more focus can be given to strategy and personalisation. We found out in the news last month that the royal family are using mainly Instagram for their social media activity. With regular posts and stories plus live streaming, it seems that they are targeting largely a younger audience. Automated content creation could be used in this case to mine various data and audience metrics, and then produce insightful data driven content to best target their consumers. There are some options starting at around just Ł6 a month free trials, meaning that even smaller businesses with no marketing budget can use these tools to increase web presence and sales. Such technology is only going to keep getting better and so the future for automated content creation is very exciting!
1.2. Audience Segmentation
Audience segmentation has proved to be crucial in increasing product or service awareness and driving the growth of a customer base. The feature basically enables marketers to divide their audiences into different categories, essentially making it easier for them to personalize the messages or advertisements. It is one of the most vital features that is provided by marketing AI. Marketing AI works by using a number of algorithms and the substantial amount of data that is provided within the digital marketing platforms in order to select the most lucrative target segments. This not only helps in optimizing the marketing budget but also in significantly increasing the lead generation. The AI operates by first collecting and integrating customer data from a number of sources such as email marketing lists, social media marketing and website traffic. The data collected can include but not limited to consumer demographics, purchase history, overall web behavior and any other important metrics that would help in understanding and grouping the potential customers. After the integration of the data, the AI would then use the predictive algorithm in order to identify patterns within the dataset. These patterns are usually based on the attributes that have been identified for the different segments and the way in which those attributes will differ between the segments. For instance, the AI is able to identify whether a specific segment that contains customers of a certain age range will have a better click-through rate on an advertisement as compared to other segments. This enables the marketer to focus on the specific tailored messages for these identified segments. The AI can help in analyzing all the possible combinations of data segments in order to provide a range of different ways in which the customers could be divided. This process may be extremely tedious and prone to human error but with the automation by AI, marketers can be sure to devote more time on making the most out of the identified segments.
1.3. Performance Analytics
After using AI to schedule posts and to understand our audience better, it was time to do a little something with our advertising. One AI tool that we found increasingly useful in our advertising strategy was the use of performance analytics. Performance analytics is the practice of analyzing both advertising campaigns and the results of these campaigns to find where best to allocate resources and funding for the most effective future campaigns. The tool we used for this was called Reveal, by Channable. The first thing we found really helpful, perhaps more surprisingly, was the continuous analysis and tweaking that was evident with performance analytics. Whereas with manual analysis, marketing specialists may become quickly engrossed in the arbitrary objective of a particular report or dataset, AI seems to have more of a progressivist aim of understanding and improvement. By that I mean to say that Reveal was consistently investigating all potential aspects of our advertising – browsing over 20 different kinds of analysis, from demographic targeting effectiveness, to keyword search analysis and shopping behavior assessments – as opposed to the more fragmentary and static snapshots of progress from manual efforts. Moreover, we found it easier to prioritize and refine our strategies as a result of AI analysis – appropriately, Reveal provides ‘strategy concepts’, which are a set of rules or tips which can inform the user’s choice of an outline in building efficient advertising structures. These cropped up when considering the results of analysis and potentially testing out a new focus or angle – in effect, we could collaboratively brainstorm effective changes to a particular advertising tactic with the expertise of AI as well. By comparison, the potential human errors experienced when adopting a strategy of manual trend analysis and decision-making was circumvented – no longer was there any danger of either, for instance, over-investigating fleeting ad success or perhaps even misunderstanding unassuming yet actually valuable trends.
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