Four Considerations Before Investing

  1. Ensure your data is ready

Are you capturing the right data?

You will not get AI results without the correct data.

Let’s say you’ve launched a new eCommerce store that’s generating revenue and gaining new customers. But the analytics platform shows that these customers are not coming back. That’s why you invest in specialized software in delivering recommended products by email to attract new customers.

The solution requires more than the user’s email address. He needs data from previous purchases, including the product category, item, price, and stock. In fact, the software may even use the actions of people with similar buying habits or similar demographic data to restrict recommended products.

Is your data clean?

Since machine learning depends a lot on the data, the cleaner, and more accurate the data, the more realistic the results will be, especially at low volumes. The machine learning results will be as good as the data provided. If you are not 100% confident in the accuracy of your data, you need to develop a plan to get clean data.

Main conclusion: the results will be as good as your data. Without clean data, accurate results are drastically reduced.

  1. Assess whether suppliers are making full use of technology

A customer was looking for a more automated form of customization using complex data sets to provide a unique experience for users of the site. The client was focused on the use of AI. However, after research and discussion with representatives from dozens of leading companies, we found that the reality was that AI was not really an important part of most products.

We don’t find this very surprising – AI is such an important topic that it is natural for companies to want to list it as part of their product.

For now, this is “copper work” for real AI applications and integrations.

Main conclusion: expect companies to promote the use of AI in their products, but really encourage them to understand exactly what it means and how it will help you, the user.

  1. Ask if your marketing stack integrates with AI solutions

Since AI depends a lot on your data, you want to know how it integrates your data sources with your AI solution.

Looking at the different AI platforms, we found that the available integrations differ significantly. Some platforms can only integrate with their own products, while others provide a native connector or connection via their API.

Main conclusion: have a complete understanding of your current marketing technology stack and how AI platforms should connect to it. Make sure that AI vendors offer direct integrations or documentation that you can provide to the developer or partner agency.

  1. Consider whether there are other areas where you can see a more direct ROI

AI is a brand new toy that some companies think they absolutely need, but you should consider whether other opportunities can offer ROI and that your company can take advantage of more quickly. They may not be sophisticated or modern, but they can offer great results.

Conclusion: If you are not using fundamental and successful marketing tactics, you can achieve immediate success using tactics such as promoting signs with marketing automation, instead of heavy weapons with AI.

Don’t chase fools

Yes, artificial intelligence is likely to change everything shortly, not just marketing. And in some cases, this may be the right choice for your company. Wherever you are, make sure you don’t get into AI just because it’s new and interesting. Make sure you can help today and get the return on investment that is worthwhile.

Artificial intelligence is coming and you must be absolutely ready. But you can’t hurry. Do the research. Do the legwork. You will not regret it.