Salesforce Data Cloud for Better Marketing Insights in 2024
When it comes to understanding and predicting customer behavior, marketers face a significant challenge.
Amidst the sheer volume of data available, finding meaningful and actionable insights can be like searching for a needle in a haystack.
Salesforce Einstein, embedded within the Salesforce Data Cloud, is one tool in the marketer's arsenal aiming to tackle this challenge.
First, let’s talk about what Salesforce Einstein does.
At its simplest, it’s an AI tool designed to analyze data.
Its job is to look for patterns and trends in customer interactions and use these to make predictions.
For example, if you’re a marketer trying to figure out what kind of product a particular customer segment might prefer, Salesforce Einstein can help by analyzing past buying behaviors.
However, it's crucial to understand that tools like Salesforce Einstein are only as good as the data fed into them. If the input data is biased, incomplete, or poorly structured, the outputs and predictions will be flawed. This is a common pitfall in the world of data-driven decision-making.
Furthermore, while Salesforce Einstein can automate certain tasks and provide insights, it doesn't replace the need for human judgment.
Marketers still need to,
AI can identify a pattern, but it can't understand why that pattern exists or what external factors might be influencing it.
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That’s where human expertize and experience come into play.
Another point to consider is that AI and machine learning models can sometimes be black boxes. Understanding why Salesforce Einstein made a particular recommendation or prediction can be challenging.
This can make it difficult for marketers to fully understand these tools, especially when making significant strategic decisions.
Is Salesforce Data Cloud a Good Fit for your Marketing Team?
First things first - if your org already uses Salesforce, data cloud can be a good consideration for your marketing team. If not, apart from cost, keep in mind investments in terms of time and training.
To effectively implement Salesforce Data Cloud and harness its full potential, it's essential to know what are your jobs to be done - what are you hiring the platform for?
This involves aligning key stakeholders and decision-makers on the desired outcomes, such as enhancing customer experiences through personalization, increasing marketing ROI, or streamlining data sources. This alignment lays the groundwork for selecting the right technologies to achieve these goals.
When identifying use cases for Data Cloud, it’s more effective to focus on tangible user experiences and pain points rather than starting with the technology itself.
Direct engagement with frontline teams and customers can reveal critical data issues impacting user experiences.
Finally, instead of going all guns blazing, experiment with a smaller dataset. Analyze and deeply measure its impact on the key outcomes you wanted - is it just helping your marketing team boost productivity or are there are actual improvements in marketing source revenue or pipeline.
While both are important, there are alternatives to data cloud if you are just focusing on productivity.
This approach ensures that Data Cloud matures thoughtfully, evolving from a departmental tool to a comprehensive enterprise solution.