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The Significance of Data Quality in Influencing the Success of Data Cloud and Salesforce AI

For an organisation to succeed in the ever-changing digital landscape, data quality and artificial intelligence (AI) must come together. Einstein, a state-of-the-art AI system, and Data Cloud work in concert within a Salesforce environment. It highlights the critical role that complete, accurate, and high-quality data play in enabling AI-driven insights and interactions with clients and prospects to reach their full potential.

This post will explore the relationship between these two new features and data quality, discussing the negative effects of poor data and how Einstein and Data Cloud can help your company grow.

What is Data Quantity?

If you’re like most people, duplicate records come to mind when you hear the term “quality data.” That’s really just the beginning. When examining the quality of data in your CRM, keep the following points in mind:

1. Completeness: Are there any significant data points missing? Do you know enough about your clients and potential clients to know what they are looking for? 

2. Accuracy: Do you possess up-to-date, accurate information about your clients and potential clients? Or would your emails be rejected because the client or potential client has already moved on to another business? Accurate data is only useful when it is complete. 

3. Timeliness: Are you keeping track of the appropriate information in a way that will allow you to speak with customers and prospects in a timely way in order to close new business or upsell? 

Bad Data Causes Bad Results

In addition to causing inefficiencies, inaccurate data also leads to time wastage, suboptimal decision-making, and needless strain on organisational resources. Even worse, those bad choices frequently result in actual financial losses for businesses.

For organizations, having low-quality data can be dangerous. To trust bad data to boost business performance, you must turn it into quality data. While there are some long-term tactics you can use to maintain high-quality data, maintaining high-quality data is a continuous process rather than a one-time event.

The Road to Improved Financial Performance Is Accurate Data

Most credit British Mathematician Clive Humby with coining the phrase, “Data is the new oil” in 2006, and as Forbes put it in 2022, “Like oil, data is valuable, but if unrefined, it cannot really be used.” 

However, unlike oil, which is a limited resource, data seems to be limitless. Based on current projections, the amount of data being created worldwide in 2023 is approximately 120 zettabytes. And that’s expected to grow to over 180 zettabytes by 2025. (One zettabyte is approximately equal to 1,000 exabytes or 1 billion terabytes, and a terabyte is 1 trillion bytes.)

It is important to note that data is subject to constant change. Companies that are leaders in their fields are utilising data to their advantage and are prepared to act when necessary. What’s more, those companies are taking proactive measures, foreseeing changes, forecasting the future, and implementing adjustments in preparation for what lies ahead. Poor data quality can still result in losses even with fast reaction times.

It should not be surprising that companies that take proactive measures to address data quality will not only have better data, but also experience a significant reduction in the financial impact of poor data quality. It should also come as no surprise that the earlier you create and implement a plan to improve and preserve data quality, the fewer problems you will run into with using your data as you work to expand your business.

Salesforce Einstein: Making Artificial Intelligence Accessible to All

The same fundamental principle of trust that has guided Salesforce for many years is being promoted by the Einstein messaging. It’s evident that Einstein is capable of producing communications and content with clients and prospects that are timely, relevant, and faster than those produced by humans. It’s also evident that all of Einstein’s creations rely on the information contained in the Salesforce instance in which they are installed.

Does anyone still remember GIGO? When computers were first used in business environments, a common misconception was that GIGO stood for Garbage In, Gospel Out. The majority of people accepted the findings of a report shared by a computer. When people realised that the computer was merely aggregating the data it had access to far more quickly than humans could, the second “G” eventually changed from “Gospel” to “Garbage.”

Is it feasible that AI is approaching the same tipping point as us? For the outcomes of AI to be reliable and worthwhile, the data being input must be accurate and full.

What's the buzz surrounding the Data Cloud all about?

Next, Salesforce Data Cloud appears. This makes it possible to segment and organise customer data from any source in a way that best suits your company’s operations. Additionally, because the platform is open and extensible, you can add data from any other source to enhance the existing data.

In the end, you can produce the optimal customer record to assist Sales, Service, and Marketing in carrying out their duties more quickly and intelligently, increasing the company’s profitability.

What are the benefits for us?

The secret to adoption, like almost everything else in this world these days, is to figure out WIIFM, or what’s in it for me.

You need to look at your own unique situation in order to respond to that question correctly. How accurate and dependable is your data? What are the most effective proactive strategies for preserving high-quality data, independent of the source?

The one unifying factor is that accurate, timely, relevant, and complete data is necessary for it to yield meaningful insights.

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