Sales activity definition
Just as every customer is unique, so is every seller. That doesn’t mean selling is a free-for-all or like the Wild West, but it does make it difficult for sales organizations to drive predictable, consistent results. A standardized, data-backed sales process can help with that, enabling teams to attract and convert steady business.
When sales organizations develop and implement a well-defined sales process with key sales activities at each stage, positive outcomes become more stable and routine.
This blog post will:
- Define sales activities, both quantitative and qualitative, with examples.
- Identify best practices for tracking sales data and using it to refine the sales process.
- Discuss how technology can enhance sales activities.
Sales activities: a definition
The term “sales activities” refers to the actions, practices, and strategies that sales reps and leaders do to attract prospects, advance them through the sales pipeline, close deals, and meet (or exceed) sales forecast goals.
Key sales activities are those that drive prospects to continue through the sales process and funnel at critical junctures. Not only do the key activities advance buyers from one stage to the next, they also generate data that can be used to identify the most-impactful activities and further refine the process.
Types of sales activities
The key types of sales activities (and the data they generate) can be categorized as either quantitative or qualitative. Neither is more important than the other — rather, the best practice is to balance the two types effectively.
Quantitative sales activities
Quantitative sales data is concrete and measurable — think key performance indicators (KPIs). There are daily and weekly sales activities, including lead-generation and pipeline activities, that are considered quantitative.
Examples of quantitative sales metrics and data include the number of calls made, emails sent, social media interactions, referral requests, proposals sent, and meetings scheduled. Based on these pieces of data, sales reps and leaders can learn valuable information about which sales activities lead to the best outcomes.
Some quantitative sales activities relate specifically to lead generation and pipeline activity. Examples of these activities include:
- Lead-generation activities: average lead response time, rate of qualified leads, volume of new leads in the pipeline, customer acquisition costs
- Pipeline activities: average sales cycle length, total won opportunities, total closed opportunities, annual contract value, conversion rate
Data analysis of those sales activities pinpoints those that drive consistent results and those that represent a weak link in the sales pipeline. When a business adapts the sales plan and processes to those results, data analysis of sales activities can measure the success of those changes.
Tracking quantitative sales data
Of the two types of activities, quantitative sales activities are easier to measure and understand. Historically, companies have used a sales activity tracking spreadsheet to document quantitative sales data. Nowadays, though, a lot of this data is manually entered into a CRM.
Quantitative sales data is only as useful as it is accurate. This is why forward-thinking organizations like Collective[i] have been developing ways to incorporate artificial intelligence (AI) and machine learning into the sales tech stack. Collective[i]’s Intelligent WriteBackTM removes the possibility of human error and increases the quality of data by automating CRM data capture.
Qualitative sales activities
Qualitative sales activity may be more difficult to identify and measure, but it can provide valuable insight into what’s driving sales performance. Unlike quantitative sales data, qualitative data is more subjective — it establishes context for better understanding the quantitative data and identifying the most-impactful activities.
Examples of qualitative-data–based sales activities dig into the factors that impact seller success. They may include:
- Understanding specific customer objections and/or what appeals to them
- Evaluating the reasons why deals do or do not progress beyond a certain stage
- Defining specific milestones for the lead-generation and nurturing processes
- Analyzing how high-performing reps are spending their time
Tracking qualitative sales data
Because qualitative activities and data are subjective, they can prove difficult to analyze and act on. Spreadsheets certainly aren’t useful for recording qualitative sales data.
This, again, is where modern tech platforms really shine. AI-enabled solutions like C[i]’s remove the guesswork. Collective[i]’s Intelligent InsightsTM, for example, replicates the judgment of top performers to point sellers toward the next and best actions they can take on a given day. C[i] RecommendsTM helps sales leaders identify the most impactful activities by analyzing data to deliver daily recommended actions as well as news and risk alerts.
Use AI to drive predictable outcomes
Organizations that effectively track sales activities and their outcomes can distinguish key sales activities from less impactful ones. Understanding how seller activity relates to outcomes helps sales teams optimize processes to streamline the sales cycle and drive consistent outcomes. Leveraging a platform like Collective[i]’s helps facilitate an end-to-end digital sales transformation based on hard data that you can trust.
Collective[i]’s sophisticated tools can track sales activities, provide insights into the pipeline, and guide sellers to the next and best actions that get more deals over the finish line. Get in touch today to learn more about how Collective[i] can work for your organization.Explore Collective[i]