Digital marketing faces a ton of daily challenges. Perpetual growth is what digital marketers aim at, as this is the only way their efforts can be justified – it has to support corporate growth.
These challenges pressure digital marketers into the search for the next big technological break or an automation product, which will allow to greatly increase the efficiency of marketing efforts. Otherwise, the only way to increase the growth rate is to scale the team. But that doesn’t work all the time – the budgets are limited, the expertise is hard to find and, to be honest, digital marketing isn’t always on top of the list of priorities for a company.
Let’s take a closer look at some of the technologies that can help digital marketing teams greatly increase the efficiency of their processes. Namely, how AI-based and machine learning tools already take over marketing. But first, let’s get one thing straight – you absolutely need to audit your processes to really know where these force-multiplying solutions can be applied.
Run a QA Checkup of Your Processes
Why is this important for digital marketing? It relies heavily on the product that it advertises. It’s pretty straightforward – building a solid digital marketing pipeline is a lot easier around a solid product.
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What a really good team of SQA engineers can do is very important, as they’re able to fix any faults that a product might have, if they haven’t yet done so. At the same time, a QA team works as an intellectual powerhouse that can help your company optimize internal processes. It’s their job to make your product work better.
Once a QA team runs through your processes and your product and optimizes it – your digital marketing team is ready to build on top of that. And here’s how AI can really boost your digital marketing efforts.
It’s a very promising AI / machine learning domain that has a great variety of applications. Semantic analysis allows machines to identify the basic language structures within text, group and process them according to requirements.
You can use semantic analysis to identify word patterns. For example, if you have a massive survey, you can use semantic analysis to extract key phrases and sentences that will allow you to quickly identify the prevalent sentiment among your customers. This could also be used to analyze social media posts and build customer research on top of that. For example, to analyze tweets with specific hashtags in bulk.
AI is perfect for this kind of applications, as it takes a lot of the guess work out of A/B testing and improves results much quicker than a human would. Simply because AI can use a relatively small data sample to try and build a prediction.
Tools like Sentient Ascend can multiply your digital marketing strategy with a very concise and straightforward A/B testing routine. You can even take it a step further and build out and implement an A/B testing plan using internal resources. There are plenty of learning materials to help you with that.
Experimenting with Automated Content
While this lineup of AI products isn’t particularly ready for full-blown implementation, it can certainly make some content types easy to create and scale.
With services like Wordsmith, you can automate content creation by providing data and building templates, so that the algorithm could easily create bite-sized content for your marketing purposes. It’s not yet good for long-form content and probably will never be. It can help with content that needs to be created on regular basis to constantly attract traffic, and potentially save you hundreds of working hours.
Speeding Up Decision Making
Decision making is always one of the most crucial parts of running a company and, for that matter, setting up a digital marketing strategy. Strategic decisions can make or break a business.
This is where AI and machine learning can help speed up the process. For example, Quill Engage helps with creating insightful reports based on Google Analytics data. What used to take dozens of hours, now takes minutes as the service runs GA data through a series of algorithms.
Services like KNIME offer a more comprehensive solution, which is initially based on AI to allow for a more detailed and scrupulous approach to data analytics.
Optimizing ads can be compared to A/B testing, where you essentially run a series of ads through various channels, compare them and refine ad content, based on preferences and user sentiment that the ads create.
Services like Zalster allow you to automate the process of selecting the best ads for your social media advertising efforts. This helps you to save time and money, as well as to expedite the process of reaching the best ad content in the shortest time possible with the help of machine learning algorithms.
Top social media outlets already roll out machine learning features, which help companies spend their advertising dollars more efficiently. For example, Snapchat recently rolled out a promising AI-based feature, which marketers can start using now.
Digital marketing is getting more challenging with every minute. Executives want to see digital marketing perform better with each and every iteration or new tool added to the set of a proper digital marketing department.
Constant need for innovation in digital marketing stems from this internal pressure that’s being generated in practically any online business. That’s why digital marketers should fully embrace the power of artificial intelligence to augment their routines and marketing tactics. Automation, machine learning and all of their abundant variations provide a plethora of optimization options – from automatic A/B tests to semi-automatic content creation.
With all of this in mind, it’s important to remember that any digital marketing team fails if it has a weak product behind. That’s why it’s important to conduct a preliminary audit of all of the internal processes, products and digital marketing efforts in order to make sure that this AI-based optimization is being initiated on a ‘clean slate’ that is the updated and perfected product or service.