As we approach the end of 2022, it’s time to look back at how things have changed since this time last year. This is a great exercise for digital marketers, who need to stay abreast of trends and keep up with the latest developments in the industry.
Here are some of the biggest challenges that digital marketers will face in 2022:
The rise of AI-powered chatbots
Chatbots have been around for quite some time now, but they’ve mostly been used by businesses as an automated customer service tool. However, as more companies begin to adopt AI-powered chatbots — which can be used for more than just customer service — their role will change dramatically. In fact, many experts predict that by 2022, most brands will have an AI-powered chatbot on their website or app that can answer basic questions about their products or services.
Customer experience management
With the rise of AI and chatbots, it’s becoming increasingly difficult to get real-time customer feedback on products and services. This is especially true if your business is B2B or if you don’t have an online store where people can leave reviews or ratings.
With Google wanting to make search results more relevant, there’s a growing focus on making the user experience better across the board. This means that sites need to be optimized for speed, usability, and navigation so that users can find what they’re looking for without having to dig too deep into the site’s structure or content architecture. This also means optimizing for voice search so you can serve up relevant content when someone asks for it using their voice alone — something that’s becoming more commonplace every day as more people use voice assistants like Google Home, Amazon Echo, Apple Siri, etc…
Lack of budget
Digital marketers are faced with many marketing challenges
in their jobs, but one of the biggest is budget constraints. Digital marketing budgets continue to increase year over year, but they still aren’t enough to cover all the needs of brands. As a result, many marketers are forced to make do with less than they need. This causes delays in projects and can lead to subpar results or even failure if not handled correctly.
Poor data quality and analytics
Poor data quality and analytics have been problems for years now, but they’re getting worse as more companies adopt AI-powered tools that rely on machine learning algorithms that only work well if they’re fed clean data sets by humans who know what they’re doing (i.e., trained professionals). As more companies begin using these tools — especially with such high stakes as fraud prevention — there won’t be enough trained professionals available to feed them what they need, leading to even poorer outcomes than we’ve seen before.
Poorly defined KPIs
Another challenge is that many companies
set up KPIs for their digital campaigns without being clear about what they expect from these campaigns. For example, if a company wants to increase the number of subscribers on its mailing list, it should set a KPI like “add 100 new subscribers per month.” But if it doesn’t define what kind of subscriber it wants — whether they need email addresses or mobile numbers or both — then it will find it difficult to achieve its goal. Similarly, if a company wants more people visiting its website, but doesn’t know how many visitors are considered good enough, then again it will find it hard to measure success against this goal.