How to Create Pitch Deck with Data Visualization

How to Create Pitch Deck with Data Visualization

Every entrepreneur knows that moment when everything depends on a single presentation. Your product is ready, your team is passionate, and your vision is clear—but none of it matters if you can't communicate your value proposition effectively. In today's fast-paced investment landscape, where decision-makers review hundreds of opportunities monthly, the difference between securing funding and being forgotten often comes down to how well you present your data. A pitch deck isn't just a collection of slides; it's a strategic narrative that transforms complex information into compelling visual stories that investors can't ignore.

When we talk about creating presentations that combine storytelling with data visualization, we're discussing the art and science of making numbers speak louder than words. This approach isn't about overwhelming your audience with charts and graphs—it's about selecting the right visual elements that illuminate your business trajectory, market opportunity, and competitive advantages. The most successful founders understand that data visualization serves as a bridge between raw metrics and emotional connection, turning abstract concepts into tangible evidence of potential success.

Throughout this comprehensive guide, you'll discover practical frameworks for structuring your presentation, selecting the most impactful visualization techniques, and avoiding common pitfalls that dilute your message. You'll learn how to balance quantitative evidence with qualitative storytelling, understand which data points truly matter to different investor types, and master the technical tools that bring your vision to life. Whether you're preparing for your first seed round or refining your approach for Series A funding, these insights will transform how you communicate your business potential.

Understanding the Foundation of Effective Pitch Decks

Before diving into specific visualization techniques, it's essential to grasp what makes a presentation truly effective. The foundation of any successful pitch lies in understanding your audience's perspective and priorities. Investors don't just evaluate your current numbers—they're assessing your ability to identify patterns, understand market dynamics, and make data-driven decisions that will scale your business.

The psychological principle behind effective presentations is remarkably straightforward: human brains process visual information 60,000 times faster than text. This biological reality means that well-designed data visualizations don't just make your deck prettier—they fundamentally change how quickly and deeply your audience comprehends your message. When you present revenue growth as a dynamic chart rather than a paragraph of text, you're not simplifying your message; you're making it more accessible and memorable.

Consider the cognitive load theory, which suggests that people can only hold a limited amount of information in working memory at once. Traditional text-heavy presentations force investors to simultaneously read, interpret, and evaluate your claims, creating mental fatigue. Strategic data visualization reduces this burden by presenting information in pre-processed formats that align with natural pattern recognition abilities. This isn't about dumbing down your content—it's about respecting your audience's time and cognitive resources.

The most compelling presentations don't just show data; they reveal insights that would remain hidden in spreadsheets and databases, transforming numbers into narratives that investors can't help but remember.

Core Components Every Data-Driven Deck Requires

Building a presentation that effectively incorporates visual data requires understanding the essential elements that investors expect to see. These components form the skeleton of your narrative, and each one presents unique opportunities for visualization. The key is knowing which information deserves visual treatment and which is better served through concise text or verbal explanation.

• Problem-solution framework: This opening section establishes market pain points and your unique approach to solving them. Visualize market size with comparative charts, show problem severity through survey data representations, and illustrate your solution's impact with before-and-after scenarios.
• Market opportunity analysis: Investors need to see addressable market size, growth trajectories, and your positioning within the competitive landscape. Use segmented bar charts to break down total addressable market (TAM), serviceable addressable market (SAM), and serviceable obtainable market (SOM).
• Business model clarity: Revenue streams, pricing strategies, and unit economics must be immediately comprehensible. Flow diagrams work exceptionally well here, showing how value moves through your system and where margin expansion opportunities exist.
• Traction and validation: This is where data visualization truly shines. Growth curves, user acquisition metrics, retention cohorts, and revenue progression tell stories that raw numbers cannot. Choose visualization styles that emphasize momentum and positive trends.
• Financial projections: Forward-looking statements require careful visual treatment. Multi-line charts comparing revenue, costs, and profitability over time help investors understand your path to sustainability while highlighting key inflection points.
• Team credentials: While primarily text-based, consider visualizing team experience through timeline graphics or network diagrams that show relevant industry connections and previous exit values.

Selecting the Right Visualization Types for Your Data

Not all charts are created equal, and choosing the wrong visualization type can obscure rather than illuminate your message. The decision about which visual format to use should be driven by the nature of your data and the specific insight you want to highlight. Understanding the strengths and limitations of each visualization type is crucial for creating presentations that communicate with precision.

Line charts excel at showing trends over time, making them ideal for revenue growth, user acquisition, or any metric where temporal progression matters. The slope of the line immediately communicates velocity of change, and multiple lines allow for powerful comparisons between different metrics or cohorts. However, avoid cluttering line charts with more than four data series—beyond that point, the visual becomes confusing rather than clarifying.

Bar charts work best for comparing discrete categories or showing composition of a whole. When presenting market share, competitive positioning, or feature comparison matrices, bar charts provide clear visual hierarchy. Horizontal bars often work better than vertical ones when category labels are lengthy, as they provide more space for readable text without rotation.

The chart type you choose is a strategic decision that either amplifies or diminishes your message—there are no neutral choices in data visualization, only intentional ones that serve your narrative or accidental ones that undermine it.

Technical Execution: Tools and Techniques

Once you understand the strategic framework and visualization principles, the next challenge is technical execution. The tools you choose and how you use them directly impact the professional quality of your final presentation. While many founders default to familiar software, the most effective presentations often leverage specialized tools designed specifically for data visualization and presentation design.

The landscape of presentation software has evolved dramatically beyond traditional slideware. Modern platforms offer sophisticated data integration, dynamic updating, and interactive elements that can transform static presentations into engaging experiences. However, more features don't automatically mean better results—the key is selecting tools that match your technical comfort level while providing the visual sophistication your content deserves.

Software Platforms for Building Visual Presentations

Your choice of software should balance three factors: ease of use, visual quality, and data integration capabilities. Traditional presentation software remains popular for good reason—it's familiar, widely compatible, and offers reasonable design flexibility. However, specialized tools can dramatically reduce the time required to create professional visualizations while ensuring consistency across your entire deck.

PowerPoint and Keynote remain industry standards, offering robust charting capabilities and extensive design control. Their primary advantage is universal compatibility—you can be confident your deck will display correctly on any system. Modern versions include improved chart styling options, though creating truly custom visualizations often requires significant manual adjustment. These platforms work best when you're comfortable with design principles and willing to invest time in refinement.

Google Slides provides the advantage of cloud-based collaboration and real-time editing, making it ideal for teams working across different locations. While its visualization options are more limited than desktop alternatives, its integration with Google Sheets allows for data-driven charts that update automatically when underlying spreadsheets change. This dynamic linking can be powerful for presentations that need regular updating with fresh data.

Specialized tools like Pitch, Canva, and Beautiful.ai offer template-based approaches with built-in design intelligence. These platforms understand visual hierarchy and automatically adjust layouts to maintain professional appearance as you add content. They're particularly valuable for founders without design backgrounds, as they prevent common aesthetic mistakes while still allowing customization. The trade-off is less granular control compared to traditional software.

• 📊 Data visualization specialists like Tableau and Power BI create sophisticated interactive charts but require exporting static images for traditional presentations
• 🎨 Design-first platforms such as Figma or Adobe XD offer maximum creative control but steeper learning curves and longer production times
• 🚀 Purpose-built pitch tools like Slidebean use AI to optimize layouts and suggest improvements based on successful funding decks
• 📈 Spreadsheet integration through tools like ChartBlocks or Infogram allows creating web-based visualizations that embed into presentations
• ⚡ Rapid prototyping tools including Miro or Mural help map out data stories before committing to final visualization formats

Design Principles That Elevate Data Visualization

Technical proficiency with software means nothing if your design choices undermine clarity. The visual design of your data visualizations should follow established principles that have been proven through cognitive science research and practical application. These aren't arbitrary style preferences—they're strategic decisions that determine whether your audience grasps your message instantly or struggles to decode your intent.

Color selection carries more weight than most founders realize. Beyond aesthetic appeal, color communicates hierarchy, draws attention, and can even trigger emotional responses. Use a consistent color palette throughout your deck, typically limited to three primary colors plus neutral tones. Reserve your boldest, most saturated color for the most important data points you want investors to remember. Avoid using color as the only differentiator—ensure your charts remain comprehensible even in grayscale, accommodating color-blind viewers and black-and-white printing.

Typography in data visualization serves functional rather than decorative purposes. Labels, axis titles, and data callouts must be immediately readable, which typically means larger font sizes than you might initially choose. A good rule of thumb: if you can't read your chart text from six feet away on a laptop screen, it's too small. Maintain consistent font families throughout your deck—typically one sans-serif typeface for clarity is sufficient.

Every design element in your visualization should earn its place by serving a clear communicative purpose—decoration that doesn't enhance understanding is just noise that dilutes your message.

White space, or negative space, is not wasted space—it's a crucial design element that gives your visualizations room to breathe. Cramming too much information into a single chart forces viewers to work harder to extract meaning. When faced with complex data, consider breaking it into multiple focused visualizations rather than creating one overwhelming display. Each chart should communicate one primary insight with supporting context, not attempt to tell your entire story simultaneously.

Strategic Data Selection and Narrative Flow

Having the technical skills to create beautiful visualizations is meaningless if you're visualizing the wrong data or presenting it in an illogical sequence. The strategic layer of effective presentations involves carefully curating which metrics to include, how to frame them, and in what order to reveal them. This narrative architecture determines whether your deck builds momentum toward a compelling conclusion or meanders through disconnected facts.

The most common mistake founders make is including every piece of positive data they possess, creating a presentation that feels more like a data dump than a strategic argument. Investors don't need to see everything—they need to see the specific evidence that supports your key claims and addresses their primary concerns. Selectivity demonstrates confidence and strategic thinking, showing that you understand which metrics truly drive your business.

Identifying Your Most Compelling Metrics

Different business models and industries have different key performance indicators that investors prioritize. Understanding which metrics matter most in your sector allows you to focus visualization efforts where they'll have maximum impact. For SaaS businesses, monthly recurring revenue (MRR), customer acquisition cost (CAC), lifetime value (LTV), and churn rate form the core metrics that deserve prominent visual treatment. E-commerce businesses should emphasize gross merchandise value (GMV), average order value (AOV), repeat purchase rate, and contribution margin.

Beyond industry-standard metrics, identify the unique indicators that demonstrate your competitive advantages. Perhaps you've achieved unusually high viral coefficients, exceptionally low churn in a typically high-churn category, or rapid payback periods on customer acquisition. These distinctive metrics deserve special visualization treatment because they differentiate your opportunity from others investors evaluate.

Context transforms numbers from abstract values into meaningful insights. Showing that your monthly revenue is $500,000 means little without comparison points. Is that growing or declining? How does it compare to similar companies at your stage? What's the trajectory? Always provide comparative context through year-over-year growth rates, month-over-month progression, or benchmarking against industry standards. Visualization makes these comparisons immediately apparent in ways that text cannot.

Constructing a Logical Narrative Arc

Your presentation should follow a narrative structure that builds logically from problem to solution to opportunity to execution. Each visualization should flow naturally from the previous one, creating a cumulative argument that becomes increasingly compelling. Think of your deck as a story where data serves as evidence supporting each plot point rather than as the story itself.

Begin with market context that establishes the problem's significance. Visualizations here should emphasize scale and urgency—how big is the problem, how many people does it affect, and what's the cost of inaction? This sets the stage for your solution by creating emotional investment in finding an answer.

Transition to your solution with visualizations that demonstrate differentiation and efficacy. If you have before-and-after data, comparison charts powerfully illustrate impact. If you're pre-launch, consider visualizing your solution architecture or user experience flow to make abstract concepts concrete. The goal is helping investors understand not just what you do, but why your approach is superior to alternatives.

Build momentum with traction visualizations that prove market validation. This is where growth curves, user testimonials represented as data points, and early revenue figures create excitement. The visual trajectory should clearly indicate acceleration—investors want to see hockey stick growth patterns, not linear progression. If your growth has plateaued or declined, address it directly with visualizations showing the inflection point your funding will create.

The sequence in which you reveal data is as important as the data itself—strategic information architecture guides investors through your logic, making your conclusions feel inevitable rather than aspirational.

Advanced Visualization Techniques for Complex Data

As your business matures and your data becomes more sophisticated, basic chart types may not adequately represent the complexity of your insights. Advanced visualization techniques allow you to present multi-dimensional data, show relationships between variables, and highlight patterns that simpler charts would obscure. However, complexity should never come at the cost of clarity—advanced doesn't mean complicated.

Multi-layered visualizations combine several data dimensions in a single chart, providing comprehensive views without requiring multiple slides. For example, a bubble chart can simultaneously show market size (bubble size), growth rate (x-axis), and profitability (y-axis) for different market segments. This density of information can be powerful when executed well, but requires careful labeling and legend design to remain interpretable.

Interactive and Dynamic Visualization Approaches

Static presentations have inherent limitations when dealing with complex datasets or when different audiences need to focus on different aspects of your data. Interactive visualizations allow investors to explore data at their own pace, drilling down into areas of particular interest. While traditional presentation formats don't support true interactivity, you can simulate it through thoughtful slide design and strategic reveals.

Progressive disclosure techniques reveal data in stages, building complexity gradually rather than overwhelming viewers with complete datasets immediately. Start with the high-level insight, then use animation or subsequent slides to add layers of detail. For instance, begin with total revenue growth, then break it down by customer segment, then show the drivers of growth in each segment. This layered approach maintains engagement while building toward comprehensive understanding.

Scenario modeling visualizations show how different assumptions impact outcomes, demonstrating that you've thought through various futures. Side-by-side comparison charts showing conservative, moderate, and aggressive growth scenarios help investors understand your thinking while showing you're not relying on a single optimistic projection. This approach builds credibility by acknowledging uncertainty while demonstrating preparedness for multiple outcomes.

Avoiding Common Visualization Pitfalls

Even experienced presenters fall into visualization traps that undermine their message. Recognizing these common mistakes allows you to avoid them proactively, ensuring your visualizations enhance rather than detract from your narrative. Many of these errors stem from prioritizing aesthetics over clarity or from unconsciously trying to make data appear more favorable than it actually is.

Chart junk refers to decorative elements that add no informational value—3D effects, excessive gridlines, ornate backgrounds, or unnecessary icons. These elements might seem to make charts more visually interesting, but they actually increase cognitive load and can distort data perception. 3D pie charts, for example, make it nearly impossible to accurately compare slice sizes due to perspective distortion. Strip your visualizations down to essential elements that serve clear communicative purposes.

Axis manipulation is perhaps the most common way presenters accidentally (or intentionally) mislead viewers. Starting a y-axis at a value above zero can make small differences appear dramatic, while using inconsistent scales across related charts prevents meaningful comparison. Always start numerical axes at zero unless you have a compelling reason not to, and if you do deviate, call attention to it explicitly to maintain trust.

The integrity of your visualizations directly reflects on the integrity of your business—any hint of data manipulation, even if unintentional, can destroy investor confidence irreparably.

• Inappropriate chart types: Using pie charts for data with many categories, line charts for non-sequential data, or bar charts for continuous distributions creates confusion rather than clarity.
• Overwhelming color schemes: Using too many colors, colors that clash, or colors without consistent meaning across slides makes your deck feel amateurish and harder to follow.
• Missing context: Presenting numbers without timeframes, baselines, or comparison points leaves investors unable to assess significance or draw conclusions.
• Inconsistent formatting: Varying chart styles, fonts, or color schemes across your deck suggests lack of attention to detail and undermines professional credibility.
• Overcomplication: Trying to show too much data in a single visualization forces viewers to work hard to extract meaning, often resulting in them giving up entirely.
• Unlabeled elements: Charts without clear titles, axis labels, legends, or data labels require viewers to guess at meaning, creating cognitive friction and potential misinterpretation.

Tailoring Visualizations for Different Audiences

Not all investors are created equal, and the visualizations that resonate with one audience may fall flat with another. Understanding your specific audience's background, priorities, and decision-making criteria allows you to customize your data presentation for maximum impact. This doesn't mean creating entirely different decks for each meeting—it means emphasizing different aspects and framing data in ways that align with each audience's perspective.

Venture capital firms typically have deep expertise in specific sectors and stages, meaning they quickly grasp industry-standard metrics and are looking for insights that go deeper. For VC presentations, you can use more sophisticated visualizations and assume familiarity with concepts like cohort analysis, CAC payback periods, and unit economics. These audiences appreciate seeing the analytical rigor behind your projections and want to understand the assumptions driving your models.

Angel investors often bring operational experience but may be less familiar with formal financial modeling. For these audiences, focus on visualizations that tell clear stories about market opportunity, customer validation, and team capability. Simplify financial projections to highlight key milestones and capital efficiency rather than detailed quarterly breakdowns. Use more analogies and comparative visualizations that relate your business to familiar success stories.

Industry-Specific Visualization Considerations

Different industries have established norms for how data should be presented, and violating these expectations can signal unfamiliarity with your market. Healthcare businesses should emphasize clinical validation data, regulatory pathway visualizations, and reimbursement models. Financial services companies need to foreground compliance considerations, transaction security, and unit economics at scale. Consumer businesses should lead with user acquisition funnels, viral coefficients, and brand strength indicators.

B2B companies require different visualization approaches than B2C businesses. Sales pipeline visualizations, customer concentration analyses, and expansion revenue breakdowns matter more for enterprise software than for consumer apps. Showing logos of recognizable customers can be more powerful than abstract market share percentages. Contract value distributions and sales cycle length trends help investors understand your go-to-market efficiency in ways that raw revenue numbers cannot.

Testing and Refining Your Visual Narrative

Creating your initial deck is just the beginning—the most effective presentations result from iterative refinement based on real feedback. Testing your visualizations with diverse audiences before high-stakes meetings reveals unclear elements, confusing sequences, and missed opportunities. This refinement process separates good presentations from exceptional ones that consistently secure funding.

Practice presentations with people unfamiliar with your business provide the most valuable feedback. Friends, mentors, or advisors who don't already understand your model will quickly identify visualizations that don't stand on their own. If someone asks "what does this chart mean?" it's a clear signal that your visualization needs revision. The goal is creating slides that communicate effectively even without verbal explanation, though your narration should add depth and context.

Track which visualizations generate questions or confusion during practice sessions. These pain points represent opportunities for improvement—either the visualization itself needs redesign, or you need to provide more context before revealing it. Sometimes the issue isn't the chart but its placement in your narrative flow. Experiment with reordering sections to see if different sequences create better comprehension.

Your deck is never truly finished—it's a living document that should evolve based on feedback, changing business metrics, and insights about what resonates with different audiences.

Measuring Presentation Effectiveness

While you can't directly measure how visualizations influence investment decisions, you can track engagement signals that indicate effectiveness. Note which slides prompt questions—this suggests interest but potentially unclear communication. Slides that generate no questions might be perfectly clear or completely unengaging. The ideal response is nods of understanding followed by strategic questions about future plans rather than clarifying questions about current operations.

Request explicit feedback about specific visualizations after practice sessions. Ask which charts were most memorable, which were confusing, and what information felt missing. This direct feedback often reveals blind spots that you can't identify on your own because you're too close to the material. Consider creating brief surveys for practice audiences to gather structured feedback across multiple test presentations.

Practical Implementation Workflow

Understanding principles and techniques means little without a practical workflow for implementation. Developing a systematic approach to creating your presentation ensures consistency, efficiency, and thoroughness. This workflow should balance perfectionism with pragmatism—your deck needs to be excellent, but spending months refining it means missing market opportunities.

Begin with content inventory before touching any design software. List all the key points you need to communicate, the data that supports each point, and the questions investors typically ask about your business. This content-first approach ensures you're building visualizations around substance rather than trying to retrofit content into attractive templates. Organize this inventory into logical groupings that will become your presentation sections.

Next, create rough sketches of how each data point might be visualized. These don't need to be polished—simple hand-drawn wireframes or rough digital mockups help you think through which chart types best serve each message. This sketching phase is where you experiment with different approaches without investing significant time in execution. Share these sketches with colleagues to get early feedback on which directions seem most promising.

Only after finalizing your content structure and visualization approach should you begin building in your chosen software. This sequencing prevents the common trap of spending hours perfecting a beautiful chart that ultimately doesn't fit your narrative. Work in drafts, creating rough versions of all slides before polishing any individual one. This holistic view helps ensure consistency and proper flow across the entire deck.

Resource Allocation and Timeline Planning

Creating a professional presentation with sophisticated data visualization requires significant time investment. Many founders underestimate this, leading to rushed execution and suboptimal results. Plan for the entire process to take 40-60 hours of focused work for a comprehensive funding deck, spread across 2-3 weeks to allow for feedback cycles and revisions.

Allocate roughly 30% of your time to content development and data analysis, 40% to visualization creation and design, and 30% to refinement based on feedback. This distribution ensures you're building on solid analytical foundations while leaving adequate time for the iterative improvement that elevates good presentations to great ones. If working with a team, clearly delineate responsibilities—typically the founder owns content and narrative while a designer handles visual execution, with frequent collaboration throughout.

Set milestone deadlines for each phase: content finalization, first draft completion, initial feedback incorporation, and final polish. These interim deadlines create accountability and prevent last-minute scrambling. Share work-in-progress versions with trusted advisors at each milestone rather than waiting until you think it's "done"—early feedback is easier to incorporate and often identifies fundamental issues that would be costly to fix later.

Beyond the Deck: Supporting Materials and Follow-Up

Your primary presentation deck should be concise and visually driven, but investors often request additional detail that doesn't fit in a streamlined pitch. Preparing supplementary materials with deeper data dives demonstrates thoroughness while keeping your main deck focused. These materials also provide valuable follow-up content when investors want to dig deeper into specific areas.

Create an appendix section with detailed charts that support your main visualizations. If your deck shows high-level revenue growth, your appendix might include breakdowns by customer segment, geographic region, or product line. If you present simplified unit economics, append detailed calculations showing how you arrived at those figures. This additional material proves you have depth behind your high-level claims without cluttering your primary narrative.

Data rooms for due diligence should include source data for all visualizations in your deck, allowing investors to verify your representations and explore data from different angles. Provide clean, well-organized spreadsheets with clear documentation of assumptions, data sources, and calculation methodologies. This transparency builds trust and accelerates the due diligence process by preemptively answering questions about data integrity.

Frequently Asked Questions

How many slides should my presentation include?

Most effective presentations contain 12-15 slides for the main narrative, with additional appendix slides available if needed. This length allows you to tell a complete story in 15-20 minutes, leaving time for questions and discussion. Quality and clarity matter far more than quantity—a focused 10-slide deck that communicates clearly is infinitely better than a 30-slide deck that loses your audience.

Should I use animation and transitions in my visualizations?

Subtle animations can be effective for progressive disclosure, revealing data in stages to build understanding. However, avoid flashy transitions or animations that distract from content. Simple fades or wipes work well; spinning, bouncing, or elaborate effects appear unprofessional. Test animations in the actual presentation environment—what looks good on your screen may be distracting on a projector or in a video call.

How do I handle sensitive data that I can't share publicly?

Create two versions of your deck: one with actual data for serious investor conversations under NDA, and one with representative data or percentages for initial outreach. You can show growth rates, trends, and patterns without revealing absolute numbers. Many successful founders use indexed charts that show relative performance without exposing precise figures.

What if my data doesn't show consistent growth or has negative trends?

Address challenges directly rather than hiding them—investors will discover issues during due diligence, and transparency builds trust. Visualize the problem clearly, then show your analysis of root causes and the corrective actions you're implementing. Include forward-looking projections showing how your interventions will create inflection points. Investors respect founders who acknowledge challenges and demonstrate clear plans for addressing them.

How often should I update my presentation deck?

Update your deck monthly with fresh data, or immediately after significant milestones or changes in business trajectory. Showing outdated metrics suggests lack of momentum or attention to detail. However, maintain consistent formatting and narrative structure across updates—don't completely redesign your deck each month. Investors who see your deck multiple times should recognize the story while seeing clear progression in your metrics.

Can I reuse visualizations across different presentation contexts?

Core visualizations showing your key metrics can and should be reused across investor meetings, board updates, and team presentations, ensuring consistency in how you represent your business. However, adjust context and emphasis based on audience—what matters to investors differs from what matters to potential employees or strategic partners. Maintain a library of visualization templates that you can quickly customize for different purposes.

What's the best way to present projections without seeming unrealistic?

Show multiple scenarios (conservative, moderate, aggressive) to demonstrate you've thought through different possibilities. Clearly label assumptions driving each scenario and explain the logic behind them. Include historical data alongside projections so investors can assess whether your forward-looking statements align with past performance. Reference comparable company trajectories to provide external validation for your growth expectations.

Should I include competitor comparisons in my visualizations?

Yes, but focus on differentiation rather than criticism. Competitive positioning matrices, feature comparison tables, and market share visualizations help investors understand your unique value proposition. Be factual and fair in competitor representations—disparaging competitors appears unprofessional and raises questions about your judgment. Emphasize what you do differently rather than what competitors do poorly.