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Marketers today strive to provide truly exceptional client experiences. Customers now want seamless, tailored brand interactions across all touchpoints. Meeting these higher expectations, however, is not a simple task.
Fortunately, marketers now have powerful new tools to help them understand and forecast customer behaviors at scale: artificial intelligence (AI) and agile methods of working. This guide offers a road map for using AI and agile marketing approaches to create outstanding customer experiences.
Step 1: Set up your data foundation.
The first step in generating exceptional experiences with AI and Agile marketing is setting your data foundation, which might be overwhelming. To overcome the difficulties of data management, many marketers have turned to agile marketing principles such as cross-functionality and incrementalism, which assist lessen overwhelm.
Determine the data required for an outstanding, tailored client experience before forming cross-functional teams. Then, figure out who in the organization represents or controls the data you require. Consider inviting the data’s representative or owner to join your team, depending on aspects such as data accessibility and depth of data required.
Including these folks in a working group or team avoids silos, back-and-forth, and turf fights, ensuring that your data is clean, consistent, and easily available. This cross-functional strategy also assists the business in promoting knowledge exchange and creating the transparent culture required to lay the groundwork for the data foundation.
While it may be tempting to make massive, radical changes to your data base, consider adopting a gradual mentality. Begin where you are and make minor adjustments over time. This prevents data initiatives from becoming bogged down in massive budget talks or hampered by coordination concerns. It is vital to establish the fundamentals of a data foundation before incorporating AI into client interactions.
Step 2: Integrate more agile approaches.
The next step is to incorporate more agile practices into your customer experience teams, such as establishing iteration. Iteration is the process of breaking down work into smaller chunks that can be provided on a regular basis, for as every two weeks. The larger the deliverable, the more likely it is to experience delays, roadblocks, or go off course. Iterations help to keep projects running smoothly and reduce hazards.
Visualizing work promotes transparency and speedy communication. The brain processes visuals at a rate 65,000 times faster than it does words. Many teams that visualize their work can clearly identify how much work is in progress and what is stalled or not going. Visualizing work fosters predictability and flexibility in marketing teams, all of which are vital for maximizing the consumer experience.
The regular cadence of iterations, paired with regular reflection moments, known as retrospectives in agile, enables teams to identify lessons learned and areas for improvement. These reflection points enable teams to continually fine-tune their strategy as they use AI capabilities to improve the consumer experience.
Step 3: Use AI analytics for customer insights.
With that in place, it’s time to figure out how you can leverage AI analytics to improve consumer insights. Will you employ predictive analytics to provide a personalized experience? Will you employ artificial intelligence techniques for sentiment analysis?
If possible, employ real-time customer activity tracking to create dynamic user personas or consumer segments. Begin with your business goals and move backwards from there. For example, if you want to increase your brand reputation, an AI sentiment analysis tool is more useful than one that predicts attrition rates. Without focus, it’s easy to get sidetracked by the next new tool.
Make time and space for your marketing personnel to investigate, learn about, and receive training on these tools. This will provide insights on customer behavior, preferences, and trends, which can be used to develop targeted marketing campaigns.
Step 4: Personalization and content optimization.
You are now ready to add personalization and content optimization. This is where agile marketing strategies such as experimentation come into play. Use the insights gained in the preceding steps to design well-structured experiments. A well-formed experiment states a hypothesis and describes how you will know if it is true or false.
Assume your AI sentiment tool detects a recent decrease in confidence among your automobile clientele. You believe that a collection of customized automobile customer stories will boost this metric. Most marketers stop there, execute the trial, and use fuzzy analytics to determine whether or not it was successful. A well-designed experiment defines these metrics in advance. You may write, “The experiment succeeds if our credibility sentiment increases by 5% and fails if it stays flat or increases by less than 2%.”
AI insights + personalization + experimentation equals continuously better customer experiences.
Step 5: Measuring results
Running well-formed experiments based on business objectives helps marketers focus on results rather than outputs. It is not sufficient to implement an AI tool. It is not sufficient to generate data and insights. It is not enough to personalize content. It is only sufficient when the customer gets a truly extraordinary experience, which must be quantifiable.
When creating your data foundation, you must examine the data required to deliver an exceptional client experience, as well as how you will measure its success.
Leveraging AI and agile marketing to create remarkable customer experiences
Creating amazing customer experiences with AI is not as simple as pursuing the newest AI technology. Marketers must consider their data foundation, deciding which data will be utilized to drive the customer experience, monitoring outcomes, and determining where that data will be stored.
Agile marketing techniques such as visualizing work and employing iterations keep work moving and provide for flexibility as marketing begins to create AI-driven customer insights. These ideas are put into action through well-designed experiments. Following this advice will allow you to mix AI with agile marketing to create unique consumer experiences.