When examining what should a sales strategy include, most leaders focus on methodology, training, and targets, but they’re missing one crucial element that separates winning strategies from costly mistakes: the control group.
Understanding what should a sales strategy include goes beyond choosing between consultative or transactional approaches. It requires building in mechanisms to test your assumptions, measure actual impact, and make strategic decisions backed by undeniable data rather than intuition alone.
Why Your “Gut Feeling” is a Deceptive Guide
Correlation Isn’t Causation on the Sales Floor
Sales leaders often make massive strategic shifts such as targeting new verticals, adopting new methodologies or changing compensation plans without a reliable way to measure their true impact. Success gets attributed to the new strategy, while failure gets blamed on external factors, but there’s no proof either way.
When considering what should a sales strategy include, data-driven decision making must be at the foundation. Here’s why intuition-based strategy fails:
Confirmation Bias Takes Over You just invested heavily in a new training program, so you’re naturally inclined to notice the wins and overlook the losses that might contradict your decision. Your brain filters information to support your existing beliefs.
Confounding Variables Cloud Results Did your revenue increase because of the new sales play, or was it because of a new product release, a competitor’s stumble, or a seasonal buying trend? Without a control group, it’s impossible to know what actually moved the needle.
The High Cost of Being Wrong Scaling a flawed strategy across an entire sales force can burn significant resources, tank morale, and set you back quarters. The stakes are too high to rely on guesswork.
Pro Tip: Document all external factors that might influence your sales results during strategy changes. Market conditions, product launches, and competitive movements all impact outcomes.
A/B Testing for Revenue: What Should a Sales Strategy Include for Real Results
Moving from the Lab to the Leaderboard
When asking what should a sales strategy include, scientific rigor should be non-negotiable. A/B testing isn’t just for marketing campaigns—it’s the key to building a predictable, scalable revenue engine.
Here’s how the sales control group methodology works:
The Control Group A segment of your team, leads, or territories that continues to operate with the current, existing strategy. This is your baseline—what “business as usual” looks like under normal conditions.
The Test Group (Treatment Group) An equivalent segment where you implement the new strategy you want to measure. This group receives the intervention you’re testing.
The Golden Rule The groups must be as similar as possible in terms of tenure, historical performance, territory potential, and other relevant factors. The only significant difference should be the strategy they’re executing.
This scientific approach answers the fundamental question of what should a sales strategy include: built-in mechanisms for validation and continuous improvement.
How to Design and Run Your First Sales Experiment
Step 1: Formulate a Clear Hypothesis
Your hypothesis must be specific and measurable. Vague goals like “improve performance” won’t give you actionable insights.
Example Hypothesis: “Having Account Executives focus on a dedicated list of target accounts will result in larger average deal sizes compared to territory-based prospecting over one fiscal quarter.”
Step 2: Define the Groups and Key Metrics
Group Selection Methods:
- Randomly assign sales reps to control and test groups
- Split territories using non-performance metrics (geography, industry, etc.)
- Give different teams separate lead queues
- Alternate time periods for the same team
Primary Metric Selection: Choose the single most important number that will prove or disprove your hypothesis:
- Win rate improvements
- Average deal size increases
- Sales cycle length reductions
- Pipeline velocity changes
Secondary Metrics for Context:
- Number of meetings booked
- Pipeline created per rep
- Customer satisfaction scores
- Rep engagement and morale
Pro Tip: Choose metrics that directly tie to revenue impact. Activity metrics are interesting but outcome metrics determine success.
Step 3: Run the Test with Discipline
Set a Fixed Timeframe: Most sales experiments need at least one full sales cycle to produce meaningful results. Quarterly tests work well for most B2B organizations.
Preserve Experiment Integrity: Resist the urge to “help” the test group or change parameters midway through. Any adjustments invalidate your results and waste the time invested.
Monitor Without Interfering: Track progress regularly but avoid making real-time adjustments. Document observations but let the test run its course.
Step 4: Analyze the Data and Make Strategic Decisions
Compare Primary Metrics: At the test’s conclusion, compare the primary metric for the Test Group versus the Control Group. Look for meaningful differences that exceed normal performance variation.
Assess Statistical Significance: Was the difference large enough to be confident it wasn’t just random variation? Small improvements might not justify the cost and complexity of change.
Consider Implementation Costs: Factor in training time, tool costs, and organizational disruption when deciding whether to scale successful strategies.
Real-World Experiments You Can Run Next Quarter
Testing New Messaging Strategies
Hypothesis: Value-based messaging will outperform feature-based messaging in initial prospect conversations.
Test Design: Give half your SDRs the new value-focused script while the other half uses the existing feature-focused approach. Measure meeting conversion rates and meeting quality scores.
What Should a Sales Strategy Include: Multiple tested messaging frameworks for different buyer personas and use cases.
Testing New Target Verticals
Hypothesis: The manufacturing vertical has shorter sales cycles than our current generalist approach.
Test Design: Assign a dedicated pod of reps to prospect only manufacturing accounts. Compare their average sales cycle to the rest of the team handling mixed verticals.
Success Metrics: Sales cycle length, close rates, and average deal size within the manufacturing vertical.
Testing New Sales Tools and Technology
Hypothesis: A new lead intelligence tool will increase the number of qualified opportunities per rep.
Test Design: Provide the tool to one team but not another equivalent team. Measure pipeline created per rep and opportunity quality scores.
Implementation Considerations: Factor in tool costs, training time, and user adoption rates when evaluating results.
Testing Compensation Plan Changes
Hypothesis: Commission accelerators for deals above a certain threshold will increase average deal sizes.
Test Design: Apply the new compensation structure to a subset of reps while others maintain the existing plan. Track deal size distribution and overall revenue per rep.
Important Note: Compensation changes require careful legal and HR consultation before implementation.
Common Pitfalls to Avoid When Testing Sales Strategies
Pitfall 1: Testing Too Many Variables at Once
Test one significant change at a time. If you simultaneously change messaging, target audience, and sales process, you won’t know which element drove results.
Pitfall 2: Ending Tests Too Early
Sales cycles take time. Ending experiments before they’ve had a chance to show meaningful results wastes the effort invested in setting them up.
Pitfall 3: Ignoring Qualitative Feedback
While quantitative metrics are crucial, don’t ignore feedback from sales reps about what’s working and what isn’t. They’re on the front lines and often spot issues before they show up in the numbers.
Pitfall 4: Not Planning for Scale
Before starting any test, consider how you’ll implement the strategy organization-wide if it succeeds. Some approaches work well for small teams but break down at scale.
Pro Tip: Create a scaling plan before you start testing. Know what resources, training, and system changes you’ll need if the experiment succeeds.
Building a Culture of Experimentation
What Should a Sales Strategy Include for Long-Term Success
The most successful sales organizations don’t just run occasional tests—they build experimentation into their DNA. Here’s how to create that culture:
Regular Testing Cycles Schedule quarterly experiments so testing becomes routine rather than a special project. This consistent approach generates ongoing insights and improvements.
Hypothesis Documentation Keep a log of all hypotheses tested, results achieved, and lessons learned. This knowledge base prevents repeating failed experiments and builds institutional wisdom.
Cross-Functional Collaboration Include marketing, product, and customer success teams in your testing discussions. They often have insights that can improve your experiments or suggest new ones to try.
Celebrating Learning, Not Just Wins Failed experiments that provide clear insights are valuable. Create a culture where teams are rewarded for well-designed tests, regardless of whether they prove or disprove the hypothesis.
Advanced Testing Strategies
Sequential Testing
Rather than running single experiments, chain related tests together. If messaging A beats messaging B, test messaging A against messaging C to continue optimizing.
Cohort Analysis
Track groups of customers or deals over time to understand long-term impacts. Some strategies might improve short-term metrics but hurt customer retention.
Multi-Armed Bandit Testing
This approach automatically shifts more resources to better-performing strategies during the test period, maximizing results while still gathering data.
Technology and Tools for Sales Experimentation
CRM Configuration
Ensure your CRM can track the data points you need for testing. Custom fields, pipeline stages, and reporting capabilities are essential for effective experimentation.
Analytics Platforms
Invest in tools that can segment performance data by different variables and track statistical significance. Basic spreadsheet analysis often isn’t sufficient for complex sales experiments.
Communication Tools
Use shared dashboards and regular reporting to keep stakeholders informed about test progress without compromising experiment integrity.
What Should a Sales Strategy Include: The Complete Framework
A comprehensive sales strategy that drives sustainable growth should include:
Testing Infrastructure
- Regular experimentation schedules
- Control group methodologies
- Data collection systems
- Results analysis processes
Hypothesis Development
- Clear problem identification
- Measurable success criteria
- Resource requirement planning
- Risk assessment frameworks
Implementation Planning
- Pilot program structures
- Scaling decision criteria
- Change management processes
- Training and support systems
Continuous Improvement
- Regular strategy reviews
- Performance monitoring systems
- Feedback collection mechanisms
- Adaptation protocols
Stop Gambling, Start Engineering Your Success
The question isn’t whether you can afford to test your sales strategies—it’s whether you can afford not to. Every quarter you operate without this framework is a quarter you’re potentially scaling the wrong approach or missing opportunities for improvement.
Making strategic decisions without clean data is just gambling with your company’s future. The most successful sales organizations treat strategy development like product development—with rigorous testing, clear metrics, and data-driven decisions.
