Sales data is the source for insights that help sales organizations make better decisions to achieve better results. Yet less than one-third (30%) of participants in our 2019 World-Class Sales Practices Study agreed they have a clear strategy for leveraging data as an asset for their organization. (Click to tweet) In a previous blog, we discussed what to keep in mind when defining a clear data strategy. Today we look at why having one matters.
Considering the state of sales technology, where organizations have an average of 10 sales technologies in place – with four or more planned within the next 12 months (2018 Sales Operations Study) – it can be overwhelming for many sales organizations to get their arms around how to use the available data across their disparate systems. In addition, the majority (75.8%) of organizations that participated in our 2019 World-Class Sales Practices Study indicated they do not have a high level of confidence in their CRM data.
Disparate systems, each with its own set of data that sales organizations do not have confidence in… It’s no wonder why many sales organizations perceive sales data to be a challenge.
But the reasons why sales data is so challenging are the same reasons why executive sales leaders need to define a clear sales data strategy and take ownership end to end. (Click to tweet)
While we won’t go into detail on how to implement a sales data strategy in this blog (to read more on this topic, click here and here), let’s revisit what we mean by sales data strategy.
A sales data strategy is a documented plan that provides sales organizations with a structured framework to effectively manage and use data as an asset. It starts with executive sales leadership owning it end to end, partnering with sales operations and IT on its execution.
Data by itself is meaningless and useless. Without the context for what you want to use it for, you won’t be clear on what analysis to compile with the available data. Your sales data strategy can provide that context. (Click to tweet)
If you’re wondering whether sales data strategy matters, the answer is yes, it does. In our 2019 World-Class Sales Practices Study, we found that organizations that said they had a clear data strategy reported higher quota attainment and win rates than those that did not. (Click to tweet)
Let’s review why sales data strategy matters by taking a look at some common challenges organizations face without one.
1.Too many reports, not enough insights. (Click to tweet) It’s common to see many reports in your CRM or other sales technologies. In fact, today’s sales technologies make it easy for anyone to create reports. This, in turn, creates a situation with many reports but not enough insights. Reports are a way to pull together available data in a more structured and organized manner; however, they’re useless without context around what insights need to be produced and when those insights will be reviewed.
Sales data strategy starts with the executive sales leader clearly defining how to use the available data. It can provide sales operations, who owns the analysis of the data, with the context needed around what to compile analysis on and when to review the insights so that sales leaders can make business decisions. With this clarity, sales operations can more effectively manage the state of available reports and create more meaningful ones with a clear outcome in mind: to compile analysis for specific insights.
2.You might unknowingly be compiling incomplete analyses. (Click to tweet) Data can reside in many systems, owned by different groups. Without clarity around where data resides and who owns it, compiling an analysis on something that sounds simple (like your “customer”) can be more challenging than you might think. You may end up compiling an incomplete analysis by unintentionally excluding the other types of “customer” data available outside of your CRM and sales technologies.
A sales data strategy can provide a structured approach to managing data. It starts by identifying who owns the available data and which system the data resides in. If you identify multiple groups owning a type of data – such as “customer” data that sales, marketing, customer success and finance each might own during different phases of customer engagement – it’s important to clarify who owns which aspect of that data. This will provide sales operations teams with clarity around which system(s) you may need to pull data from for your analysis.
3.Your sales operations team may not be equipped to manage data and compile insights. (Click to tweet) With data residing in multiple disparate systems and sales not having confidence in available data, there’s a lot of work to be done – from managing data quality to overseeing process and system integrations to compiling analysis and delivering insights. Without the right capabilities in place – both technology and skill-wise – your sales operations team will soon be overwhelmed with all that needs to be addressed.
A sales data strategy should include planning for the necessary investments across technology and skills to support ongoing data quality management, analytics-based insights, and process and technology integrations. Once a sales data strategy is defined, it’s important for sales operations leaders to assess the state of their sales operations capabilities. This is an important step to ensure they are equipped to support the defined sales data strategy on an ongoing basis.
With a clearly defined strategy for leveraging data as an asset, sales and sales operations leaders will be able to bring a state of order to what may appear to be a chaotic situation. (Click to tweet)
Sales leaders can ensure the sales data strategy they define can be executed against, by driving alignment on how to use available data, taking a more structured approach to managing data and ensuring the needed capabilities are in place. This, in turn, will allow sales operations leaders, in partnership with IT, to more effectively execute against the sales data strategy – from managing data quality, to compiling insights that help drive business decisions.
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