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MarTech » Marketing artificial intelligence (AI) » 4 AI categories impacting marketing: Personalized customer journeys
In this four-part series, we’re exploring four categories of artificial intelligence (AI), how they can meaningfully impact marketers and their customers and what to potentially avoid. Part one (Generative AI) is here, and Part two (Predictive Analytics) is here.
AI has great potential to assist brands in providing the personalized customer experiences consumers increasingly expect. While many brands have started their own journey with personalized customer journeys, few have reached the holy grail, which is an end-to-end, omnichannel, orchestrated and personalized customer journey. 
In this third article of the series, we will look at personalized customer journeys, how artificial intelligence is integral to them and the platforms and tools that make them possible.
When we talk about personalized customer journeys, we mean going beyond simple marketing automation, where the customer experience is tailored to provide the “next best action” for the individual based on their behaviors and propensity to engage/buy specific products and services. Utilizing AI and machine learning, these platforms and methods put the customer at the center of the action.
The following types of platforms often enable personalized customer journeys:
These platforms rarely work in a vacuum, however. In addition to those mentioned above, there will need to be customer data (often utilizing a customer data platform, or CDP, and a CRM and purchase history), plus integrated channels that can be orchestrated and automated. 
In other words, there needs to be an ecosystem where the “brain” is a CJO or real-time decisions or next best action platform and a whole suite of tools that tie customer data to the communication channels the customer is likely to use. This can be any number of channels (e.g., email, website, mobile app, SMS, social media, etc.), and to truly reach omnichannel, a brand must interact with customers on all channels.
There are several reasons why brands need to pay particular attention to the area of personalized customer journeys. Here are a few things to note and why so many 
Consumers now expect to have personalized content and experiences, and they reward brands that provide them with repeat business. 
Customers are using multiple devices before, during and after the buying process, and brands that are tuned into this behavior win loyal customers by getting them what they want, when, where and how they want it.
While many brands are just getting started with some of the tools mentioned earlier in this article, the platforms themselves are, in many cases, mature and ready for enterprise use. 
There are some very good reasons to focus on creating personalized customer journeys. With AI-driven tools growing in their sophistication and ability to integrate across channels, this area is set for a lot of growth in the coming months.
Omnichannel, personalized customer journeys across the entire buying (and post-purchase) experience may be out of reach for many brands in the near term, but that doesn’t mean you can’t make significant progress here by utilizing some AI-based tools (as well as some non-AI-based ones). 
Let’s explore a few ways brands can take some first or next steps. Just remember that personalized journeys become more effective the more channels they reach and the more comprehensively they span the entire experience of being a customer.
To take some initial steps towards personalized customer journeys, brands can do the following:
When you approach the creation of personalized journeys in this way, your adoption of AI to improve the customer experience can be done in a meaningful yet incremental way that lets you learn quickly and apply those learnings more broadly as your programs expand.
As exciting as this area of AI may be, there are a few things to watch out for in the rush to build a personalized customer journey.
These could be teams that need to work together to support an omnichannel experience or data silos, platform silos, or all of the above. Delivering an omnichannel experience takes a lot of coordination, so tackle this from the start.
While this is an exciting area, there is a lot of data, teams and platforms to connect, and it can be easy to try to do too much without testing and improving over time. Don’t start too broad without trying to learn from early tests, even if you only look across a few channels or a small section of the overall customer journey. This is also important when incorporating AI and machine learning models into your personalization, as these models also take time to learn the best approaches.
Make sure the customers stay in control and can “opt out” of a journey and into another one. This is a balancing act between a brand dictating what they would like to happen, AI recommending what seems like the best fit and a customer choosing what they want.
Taking care to avoid common pitfalls can ensure greater success for you and your customers as they embark on the personalized journeys you create for them.
Personalized customer journeys hold much current and future potential and are a strong area to consider utilizing artificial intelligence. While tying together a complete personalized customer journey can take a lot of coordination between teams, data and platforms, the results for the customer can be incredibly valuable.
In the next and final article in this series, we’ll explore a fourth area where AI can impact marketing teams and their work: workflow and task automation.
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Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.
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