Data-driven insights for sales prospecting create a huge advantage for teams using an outbound strategy. By supporting your sales prospecting efforts with detailed and accurate information, you make life easier for sales reps, boost productivity, stay ahead of the competition, and drive business forward. Insights can help you build strategy, accurately forecast sales, and make […]
Data-driven insights for sales prospecting create a huge advantage for teams using an outbound strategy. By supporting your sales prospecting efforts with detailed and accurate information, you make life easier for sales reps, boost productivity, stay ahead of the competition, and drive business forward. Insights can help you build strategy, accurately forecast sales, and make sound business decisions. So how do you ensure that data-driven insights power your business strategies? Let’s take a look at how companies are doing it today and where the future of B2B data prospecting is heading.
The dawn of data insights
With recent advances in AI, we have only just begun to understand how it allows new ways of making business decisions.
The role of data insights in today’s business landscape
Data collection, research, and analysis is essential to every modern company. From recording expenses in an Excel to running sophisticated, AI-enhanced modeling, digital data is used constantly by anyone in business.
Moving from data to insights is the next step for many organizations. We’re constantly creating new ways of performing analyses to make all of that information more meaningful. Some of the most common applications of business data insights include risk assessment, performance tracking, and operations.
How data-driven decision-making impacts sales strategies
There are countless data-driven applications for sales, such as:
- Improved customer understanding
- Targeted marketing
- Optimized sales processes
- Real-time sales insights
In fact, the use of data insights has grown to the point where, according to Accenture, approximately 90% of all business strategies include some use of digital information. The way companies apply it could be one of dozens (or hundreds) of possibilities – the options for digital applications are practically endless. But the main idea here is that making important business decisions is pretty much synonymous with data analysis nowadays.
But this doesn’t mean that a lot of companies are leaning on data just because everyone else is doing it. Business information analysis does pay off, as Accenture reports: the average data-driven enterprise grows by 30% per year. The bottom line benefits from an emphasis on data too; McKinsey states that B2B companies with a data-driven sales operation have enjoyed a 20% increase in income.
Data insights in decision-making
So, what are all of these companies doing differently with data today than they were 20 years ago? Instead of using information as a way to describe a situation, such as in statistical analysis, modern organizations are leveraging data to make crucial decisions, both strategically and in day-to-day operations.
Definition of data insights and their role in sales prospecting
Data insights are the understanding an individual or team gains from analyzing and interpreting data. The difference between data and data insights is that data is just a collection of facts, whereas insights are the knowledge that comes from analyzing data based on patterns that are recognized by people or software.
In the hands of teams that are part of an outbound sales strategy, data insights have a particular value during the process of sales prospecting.
Benefits of leveraging prospecting data insights
Sales prospecting takes time. Even if you have lots of fabulous data about prospects, you’re still going to spend hours trying to nurture contacts who are simply not in the market for your product. This waste is compounded when you’re not sure of the best time of day, messaging, or personalized approach to use for individual prospects.
Data insights can turn this situation around by enabling:
- Automatic updates of ideal customer profiles (ICPs). Some prospecting tools will automate the process of adjusting ICPs based on firmographic, technographic, and demographic data, which ensures that your team is researching the right kinds of prospects.
- The setting of practical schedules. Part of the sales planning process is setting goals. Data insights can follow the team’s actual progress to help you understand how long it takes to complete tasks. This will allow you to set targets and build schedules according to realistic conditions instead of wasting time going for the impossible.
- Faster reactions to changes in the market. Modern data insight platforms keep track of major industry and company events. With a good overview of what’s happening to prospects, you’ll be able to plan ahead instead of relying on yesterday’s information.
- More efficient connection processes. When starting a prospecting campaign, you might have no idea of the best way to get in touch with prospects. But, with information analysis, you’ll soon see which methods are optimal for successful prospect engagements.
Use cases and examples
The uses of data insights are not hypothetical, and many organizations are achieving impressive results with them today. Here are a few examples that stand out:
- Social media listening. Monitor social media platforms for relevant keywords and product names. What are the conversations around those keywords? How often are they talking about those topics? These data points will help your sales team to identify prospects and pain points.
- Behavioral analytics. By examining the prospects’ behavior, sales teams can figure out how to respond in certain situations. For instance, if you don’t hear back after a first call to a prospect, how long do you wait to call again? Take a look at your data to see what time frame has produced the best results.
- Engagement analysis for improved performance. You can use data insights to see which tactics get the best reaction from your prospects. Monitoring email open rates, click-through rates, and responses can provide insights into the effectiveness of outreach campaigns. Insights will enable you to determine which messages and approaches increase conversion rates the most.
Leveraging intent data to prioritize prospects with high purchase intent
Intent data is a super powerful kind of data that can give you valuable insights about who is most likely to buy. With intent data, you can see which companies are actively searching for specific topics related to your product. For example, if you sell CRM software, that’s not something companies are game to rip and replace at any given time. So if you’re prospecting blindly, it can be a hard sell if they’re already settled into a CRM that works fine (even if they’re not in love).
With intent data, you can see “scores” that rank companies’ intent. The higher the score, the more they’re doing activities that show they’re interested in your solution. With that data, you can gain insights that help you prioritize your prospecting list. Those companies with a high intent score are actively looking for a CRM (or at least, feeling the pain of an imperfect fit and considering their options). Since you have data that shows they’re currently in the market for your solution, you can push them to the top of your priority list.
Analyzing industry trends and triggers to identify prospects in active buying cycles
Data insights aren’t only built on information about individual prospects. Industry-wide trends can also tell you if and when companies are more likely to purchase certain products. For instance, if the outlook is good for sales in a certain industry, a potential insight to take from that data could be that companies are looking for scalable business software to accommodate their growth.
Top data insight platforms
In this digital age, it’s basically essential to use data to optimize your sales strategies. And there are many sales prospecting platforms on the market that can help you with getting the data (and insights) you need. But not all platforms are created equal, and it’s important to take the time to figure out which one is the best fit for you.
Leading data insight platforms for sales prospecting
Some business data suppliers are large and well-known, while others are new and specialized. But the provider you choose should always come with up-to-date information–including the small details–regarding specific decision makers in target companies.
Overview of key features and functionalities offered by each platform
Here are some of the top business intelligence platforms, with a brief comparison of each:
- Lusha – the sales intelligence platform features 100 million business profiles, intent data signals, direct contact data, and a self-service interface in addition to an enterprise platform.
- Apollo – the data supplier gives you access to 10 million company profiles and has a relatively complicated interface; however, they provide direct contact information.
- UpLead – the organization sources 62 million business profiles and provides mostly email addresses.
Best practices for using data insights in sales prospecting
To get the most out of data insights, you need to ensure two things: one, that the data is recent and relevant, and two, that you have the right processes in place to take full advantage of it.
Importance of data quality, integration, and analysis for successful outcomes
Personalization is essential for a successful prospecting strategy. Teams should have a large number of details about prospects before they contact them. A common way to get this information is through business intelligence data vendors, and you should make sure to choose the right one for your needs (see above).
However, such data is not useful on its own. At the very least, it should be integrated with a scoring method for a prospecting list that allows the sales team to prioritize and divide prospects among themselves. Also, you’ll need to record the progress of engagement with prospects, so you need to integrate with your CRM.
Personalization and prioritization are two functions that should be ongoing. Both before and after approaching a prospect, your team should record all their interactions and the messaging that they used so that you can identify trends and make future efforts more efficient. Data collection and analysis can tell you what kinds of prospects are converting at the highest rate, what value propositions they respond to, and what communication channels are best for reaching them.
Tips and strategies for incorporating data insights into sales prospecting
Leveraging data insights for sales prospecting can significantly increase your chances of success. Although your organization is likely to have a list of recommendations for working with data insights, here are some tips that tend to be common best practices.
- Ideal Customer Profile. Start by creating a clear and detailed ICP based on historical data of the kinds of prospects with the highest conversion rates. This will come in handy for your data analysis, since you’ll know what kind of prospects you want to go after.
- Data collection and enrichment. If you’re going to be making insights from data, you need to make sure that data is good to begin with. A lot of times your data might be incomplete (or old), so you’ll need to find a data enrichment platform to fill in the blanks.
- Segmentation. Analyze the data you’ve collected and refer to the ICP to get insights about your prospects’ likelihood to buy. Then prioritize each according to how the data reflects their conversion potential and send it off to sales as part of their outbound efforts.
- Feedback. Collect feedback from the sales team about the quality of the prospect lists that they have received. If you believe that improvements can be made, you might try A/B testing of different messaging, altering the ICP, or reevaluating how you have prioritized the prospect list. In fact, your data might show what
Future trends
As we mentioned at the outset, technological advances have made data insights more effective than ever. This trend is expected to continue due to progress in several fields, including:
Predictive analytics. This developing technology will allow you to go beyond simply analyzing data. Predictive analytics will forecast sales trends and even provide recommendations to a company about how to meet their sales goals.
Machine learning. Advanced applications of machine learning can analyze historical data about prospects to identify patterns and characteristics that indicate the likelihood of conversion.
AI-driven solutions for enhanced prospect identification. These are often existing processes that are made more efficient by AI, such as automated intent detection, and automated prospect qualification.
Unlock the power of sales data insights with Lusha
Finally, it’s important to remember that companies don’t sit still. From different managers to new contact data to revised strategies, an organization’s details can change often – and data insights can only be reliable if data is too. The best insights come from having information that’s super fresh, so it’s essential to prioritize continuous enrichment. Learn more about Lusha’s CRM data enrichment to keep your data in tip-top shape and ready for insights.
Key takeaways
- Data insights for sales prospecting can make a significant difference to teams by expediting the entire process of identifying prospects and optimizing outreach methods.
- Making the most out of sales intelligence depends on data that enables personalization; a method of scoring your prospecting list; and a continuous effort to analyze information and optimize processes.
- You should choose an outstanding sales intelligence platform that combines volume of contacts with quality of data and ease of use.
