What is sales intelligence? Definition, tools & trends

In sales, success is about working smarter, not harder. That's where sales intelligence comes in. But what is sales intelligence, what makes it different from other tools, and why is it essential for sales teams?

In this guide, we'll break down the key concepts with an eye toward the future. Whether you're an AE looking to improve your email prospecting skills or a manager looking for new ways to improve sales team productivity, you'll learn what sales intelligence really means, the types of data that power it, how AI is transforming the category, and actionable strategies to make sales intelligence work for your team.

What is sales intelligence?

Sales intelligence is the practice of collecting, consolidating, and analyzing data from a variety of sources for actionable insights that improve performance and revenue. Typically, this requires the use of sales intelligence tools, which equip sales leaders, managers, and reps with relevant information about the people and organizations with which they engage.

It may sound like a complex process, but the main objective of sales intelligence is to help sales teams gain a full picture of workflows, prospects, and the entire revenue cycle.

Why is sales intelligence important?

Sales intelligence provides real-time data and insights, enabling sales teams to make informed decisions quickly, personalize their outreach, and stay ahead of competitors. This data-driven approach also helps teams prioritize leads, tailor their strategies, and engage prospects more effectively.

Sales intelligence optimizes the entire sales process, from lead generation to closing deals. It automates data collection and analysis, freeing up valuable time for salespeople to focus on high-value activities. Ultimately, it leads to shorter sales cycles, improved conversion rates, and a stronger competitive position in the market, making it an indispensable tool for achieving sustainable growth.

The business case for sales intelligence continues to strengthen. The global sales intelligence market is projected to grow from $4.85 billion in 2025 to $10.25 billion by 2032, reflecting an 11.3% compound annual growth rate. This growth is driven by organizations recognizing that data-driven sales strategies consistently outperform intuition-based approaches.

Sales intelligence and ideal customer profiles (ICPs)

Identifying and targeting your ideal customer is vital to a strong sales process, a shorter sales cycle, and higher revenue. Sales intelligence helps you get the information you need quickly and at scale. 

By leveraging sales intelligence tools and data, you can analyze key characteristics of your most successful customers, including industry verticals, company size, technology stack, and buying behaviors. This data-driven approach allows you to identify common patterns and attributes that define your best-fit customers, helping you create a more accurate and detailed ICP.

What is an ideal customer profile (ICP)?

An ideal customer profile (ICP) is an in-depth summary of your company’s perfect buyer. It should contain pain points and how they’d benefit from your solution. 

An ICP goes beyond basic demographics to include specific characteristics like:

A well-defined ICP can help your sales team quickly identify high-potential leads, personalize messaging, and reduce time spent chasing after prospects that aren’t the right fit. 

Remember, your ICP isn't set in stone. It should evolve as your company grows and markets shift. Regular reviews and updates, informed by ongoing data analysis, are crucial.

How to create an ideal customer profile

Building an effective ICP requires combining quantitative data analysis with qualitative customer insights. Here's how to approach it.

Identify your best current customers

To create your ICP, start by looking at your current client base and identify any common qualities. For example, do your customers tend to be in certain industries or have common job titles? 

Go beyond surface-level characteristics and analyze which customers bring the most value to your business. Consider factors such as revenue generated, longevity of the relationship, and frequency of purchases. Sales intelligence platforms can provide valuable data to support this analysis, offering insights into customer behavior and engagement patterns.

Gather customer insights and analyze patterns

Once you've identified your best customers, gather qualitative feedback on why they chose your solution and what problems it solved. Combine this with quantitative analysis to find common traits among your most successful accounts, such as industry, company size, and the specific challenges they face.

Develop your ICP description

Equipped with all the necessary information, build your ICP template. Be sure to include these key criteria: industry, company size, pain points, budget, existing systems, business objectives, buying process, how they found your business, and decision-maker job titles. Leverage sales intelligence to validate and refine these criteria, ensuring your ICP is based on the most up-to-date and comprehensive market information available.

How sales intelligence works

Sales intelligence works by gathering information from multiple sources, including native and third-party tools. The result allows sales reps to monitor engagement and key buying signals at both the individual prospect and broader account levels.

Internal data sources

Internal data, ranging from customer interactions to sales history and CRM records, plays a pivotal role in crafting effective sales intelligence strategies. To leverage this data effectively:

1. Analyze past sales performance: Identify patterns in successful deals, such as the average sales cycle length, common objections overcome, or most effective upselling strategies.
2. Mine customer support tickets: Look for recurring issues or feature requests that could inform product development or reveal untapped market needs.
3. Examine email and call analytics: Track response rates, preferred communication channels, and optimal times for outreach to refine your engagement strategy.
4. Utilize win/loss analysis: Conduct post-mortem reviews on both won and lost deals to understand what factors influenced the outcome and how to improve your approach.
5. Cross-reference customer data: Look for correlations between customer attributes (e.g., industry, company size) and metrics like lifetime value or churn rate to refine your ideal customer profile.

By systematically analyzing these internal data sources, you can uncover valuable insights to guide your sales strategy, improve lead scoring, and enhance your overall sales intelligence efforts.

Real-time data access

Real-time data allows sales teams to stay ahead of market changes, respond quickly to customer needs, and make informed decisions at every stage of the sales process. 

With instant access to the latest information about the company and its employees, reps can tailor their approach on the spot. Real-time insights also enable sales teams to prioritize leads more accurately, personalize their outreach, and identify potential opportunities or risks as they emerge.

6 Types of sales intelligence data

Effective sales intelligence combines multiple data categories to build comprehensive prospect profiles. Understanding these data types helps teams prioritize which insights matter most for their sales motion.

1. Firmographic data

Firmographic data describes the structural characteristics of target companies. This includes industry classification, company size, number of employees, annual revenue, geographic locations, and growth stage. Sales teams use firmographics to segment their total addressable market and match prospects with reps who specialize in specific territories or verticals.

2. Contact data

Contact data identifies the individuals within target accounts who influence or make purchasing decisions. Key data points include names, job titles, department, direct phone numbers, email addresses, and social media profiles. Accurate contact data enables reps to reach decision-makers directly rather than navigating through gatekeepers.

According to research from Marketing Sherpa, B2B contact data decays at approximately 2.1% per month, translating to roughly 22.5% annually. This rapid decay makes real-time data verification essential for maintaining effective outreach.

3. Technographic data

Technographic data reveals the technology stack a prospect's company uses, from their CRM and marketing automation platforms to their cloud infrastructure and security tools. This intelligence helps reps understand current workflows, identify integration opportunities, and position their solution against existing tools. 

For example, knowing a prospect uses a competitor's product allows reps to prepare relevant battle cards and competitive positioning.

4. Intent data

Intent data tracks online behaviors that signal buying interest. This includes content consumption patterns, product research activities, competitor comparisons, and engagement with industry publications. Intent signals help teams identify actively in-market accounts, enabling reps to prioritize outreach to prospects showing genuine buying behavior.

When combined with AI-powered prospecting tools, intent data allows teams to engage prospects at precisely the right moment in their buying journey.

5. Trigger event data

Trigger events are company changes that create sales opportunities. These include leadership changes, funding announcements, mergers and acquisitions, office expansions, new product launches, and regulatory shifts. Monitoring trigger events allows reps to reach out with timely, contextually relevant messaging.

For instance, when a prospect company announces a new funding round, sales teams can position their solution as essential for scaling operations during the growth phase.

6. Behavioral data

Behavioral data tracks how individual prospects interact with your company across touchpoints. This encompasses website visits, content downloads, email engagement, webinar attendance, and social media interactions. Behavioral insights reveal which topics resonate with specific prospects and indicate their position in the buying journey.

Where does sales intelligence data come from?

Sales intelligence platforms aggregate information from diverse sources to build comprehensive prospect profiles. Understanding these data sources helps teams evaluate provider quality and ensure compliance with privacy regulations.

Public records and company filings

Public data forms the foundation of most sales intelligence. This includes company websites, press releases, SEC filings, patent registrations, job postings, and social media profiles. While freely available, manually collecting this information at scale is impractical for most sales teams.

Proprietary databases

Sales intelligence providers maintain extensive databases built through years of data collection, verification, and enrichment. These databases often contain contact information, organizational charts, and technology usage data that would be difficult to obtain through other means. The best providers employ dedicated research teams to verify data accuracy rather than relying solely on automated web scraping.

Website visitor tracking

IP identification and tracking technologies reveal which companies visit your website, even when individual visitors remain anonymous. This first-party intent data indicates active interest in your solutions and helps prioritize accounts showing research behavior. Tools that identify website visitors provide valuable signals for timing outreach.

Third-party data partnerships

Sales intelligence platforms often partner with intent data providers, business information services, and industry publications to enrich their offerings. These partnerships expand coverage and provide specialized data types like technographics or financial information that would be expensive to compile independently.

CRM and internal systems

Your existing customer data provides crucial sales intelligence. Historical deal information, support tickets, product usage patterns, and communication logs reveal what success looks like for your organization. Analyzing this internal data helps refine ideal customer profiles and identify expansion opportunities within existing accounts.

Integrating these internal sources with external sales intelligence creates a unified view that revenue operations teams can leverage for territory planning and resource allocation.

Benefits of sales intelligence for today’s sales teams

In short, sales intelligence helps teams work smarter, not harder. Let’s explore the specific advantages when comparing sales intelligence to more manual ways of gathering important prospect and customer details. 

Identify high-value opportunities

Sales intelligence helps teams identify and prioritize high-value opportunities, focusing their efforts where they're most likely to pay off. By leveraging sales intelligence, reps can spend less time on low-potential leads and more time nurturing relationships with accounts that are most likely to convert into significant deals.

Personalization of sales strategy 

Sales is a science, with advanced tools that help leaders gain a more accurate picture of the pipeline and sellers to better understand how their efforts drive outcomes. But the art of properly engaging customers through personalized interactions remains a valuable skill. Research from Epsilon found that 80% of customers are more likely to purchase from a company that offers personalized experiences.

The challenge is scaling personalization across hundreds or thousands of prospects. Sales intelligence solves this by providing the contextual data reps need to craft relevant messages efficiently.

Personalization requires clean, accurate data that helps you identify decision makers, access relevant buying signals, and determine how your solution can solve specific pain points. Sales intelligence helps reps do just that, with up-to-date information that effectively guides a more personalized sales strategy.

Create comprehensive customer profiles  

By aggregating data from multiple sources, sales intelligence helps paint a fuller picture of each prospect. This goes beyond basic firmographics, pulling in technographic information, social media activity, and even buying intent signals. 

With this information, teams can tailor their approach to each account, crafting messages that resonate and proposing the most relevant solutions.

Clearer total addressable market

Understanding your total addressable market (TAM) is crucial for keeping reps as focused and productive as possible. TAM represents the total amount of revenue that your company can gain from selling its products and/or services. 

While most sales organizations present this number in terms of revenue, others view it as the total number of companies that could potentially become customers. Sales intelligence software helps uncover TAM by analyzing your existing customer information and identifying any trends. From there, your team can develop buyer personas that help them find and reach more businesses that match those personas. 

The result is better-defined budgets, more accurate growth forecasts, and easier audience segmentation for effective marketing strategies.

Identify the best time to engage through trigger events

If your reps don't know whether a prospect is ready or willing to buy, they're likely wasting time chasing dead ends. Sales intelligence monitors trigger events that create natural openings for outreach.

Trigger events are company changes that signal potential buying opportunities.

With sales intelligence, sellers discover the exact right time to contact a prospect because the platform continuously monitors company websites, social media profiles, news sources, and industry publications for these signals.

For example, if a prospect announces a new funding round, your sales intelligence software alerts reps immediately. They can then reach out with messaging that addresses common post-funding challenges, such as scaling operations or improving sales efficiency, rather than generic pitches that ignore the prospect's current context.

This timing advantage compounds over time. According to Outreach's Sales 2025 report, Outreach users who close deals within 50 days achieve twice the average market win rate. Trigger-based outreach helps teams engage earlier and move faster. 

Tools like Outreach’s Deal Agent take this further by continuously monitoring deal health, surfacing risks before they derail opportunities, and recommending actions that keep deals progressing toward close.

Access to real-time data

Sales reps are busy people: In fact, they only spend about 23% of their time actually selling. They simply don’t have the time to research each prospect’s business and industry trends and keep detailed records of that information in their CRM or other database. 

Sales intelligence software helps them stay up to date by aggregating all relevant data into a single, easy-to-consume place. Some tools display social feeds for the account or prospect, including real-time tiles for LinkedIn Sales Navigator, company Twitter profiles, and company information from Crunchbase. 

They also present company news, local time, and historical interaction with each prospect or account; all of which help to ensure effective, coherent communication.

Sales strategy improvements

It’s never enough to simply develop a sales strategy and call it a day. To ensure success, sales leaders and managers must continually refine their strategies to reduce inefficiencies, boost productivity, and, as a result, improve the bottom line. 

But those improvements require deep knowledge into how sales and marketing efforts are received, individual rep performance, process issues, opportunity gaps, and more. A modern sales intelligence platform helps teams uncover valuable insights into their process to identify what’s working, what’s not, and experiment with new initiatives. 

The result is stronger, data-driven strategies that yield better outcomes.

Guide product development 

Sales intelligence serves as a vital feedback loop for product teams, offering insights into customer needs and pain points. This information enables companies to refine their offerings and stay ahead in the market.

How to implement best sales intelligence software in your sales strategy 

Sales intelligence can be a game-changer, but knowing where to start can be challenging. Next, we’ll walk you through practical steps to seamlessly integrate sales intelligence into your existing processes.

Build accurate customer profiles 

Sales intelligence empowers you to create customer profiles that go far beyond basic demographics. By leveraging data from multiple sources, you can uncover insights into a prospect's buying behavior, pain points, and decision-making processes. With more accurate profiles, you can focus your efforts on high-potential opportunities.

Enhance sales prospecting 

Sales intelligence enhances sales prospecting efforts by providing actionable data. For example, you can use technographic information to identify companies using complementary technologies, or leverage intent data to spot businesses actively researching solutions in your space. 

Financial data can help you focus on companies with the budget to invest, while firmographic details ensure you're targeting the right company size and industry. 

By combining these data points, you can create highly targeted prospect lists.

Identify cross-selling and up-selling opportunities

Sales intelligence solutions help you identify opportunities within your existing customer base. By analyzing usage patterns, purchase history, and engagement data, you can spot trends that indicate a need for additional products or services. 

For instance, a spike in user activity could signal a need for an upgraded plan. These insights allow you to approach customers with timely, relevant suggestions that add value to their experience and boost your revenue.

Improve sales forecasting

Sales intelligence platforms can improve your sales forecasting. These tools analyze historical data, current pipeline information, and external market factors to generate more reliable projections. By considering variables like deal velocity and win rates, you can anticipate potential roadblocks or opportunities with greater precision.

Sales intelligence vs. sales enablement: Key differences

Sales intelligence and sales enablement serve distinct yet complementary roles. Sales intelligence focuses on gathering and analyzing data to provide actionable insights about prospects, markets, and trends. In contrast, sales enablement equips reps with the tools, content, and training needed to effectively engage with buyers. 

For example, while a B2B sales intelligence platform might reveal that a prospect is expanding into a new market, sales enablement ensures reps have the right pitch deck and product knowledge to capitalize on this opportunity. 

By aligning sales intelligence insights with enablement resources, companies can create a powerful feedback loop that continuously improves both strategic decision-making and frontline execution.

How to choose the right sales intelligence platform

Not all sales intelligence platforms are created equal, so it’s important to closely evaluate each before you make an investment. Here are some areas to consider.

Data accuracy and integrations  

Outdated or inaccurate information can lead to wasted time, missed opportunities, and damaged credibility. When selecting a sales intelligence platform, prioritize those with robust data verification processes and frequent updates. 

It’s equally important to make sure the platform integrates seamlessly with your existing sales tech stack. A well-integrated system allows for smooth data flow between your CRM, email tools, and other sales applications, creating a unified workflow.

Data compliance and privacy

Regulatory compliance has become a critical evaluation factor for sales intelligence platforms. GDPR, CCPA, and similar regulations govern how personal data is collected, stored, and used. Non-compliance carries significant financial and reputational risks.

When evaluating providers, verify their data sourcing practices and compliance certifications. Reputable platforms implement strict data governance measures, obtain proper consent where required, and provide transparency about data usage. They should also offer data deletion capabilities to honor individual privacy requests.

Beyond legal compliance, ethical data practices build trust with prospects. Buyers increasingly scrutinize how companies obtain their contact information, and aggressive data practices can damage relationships before they begin.

Bring intelligence to workflows

Sales intelligence solutions simplify workflows by guiding teams to improve their performance and deliver better customer experiences. 

With a complete, unified view of revenue data, continuous end-to-end revenue system inspection, and easy-to-digest data that illustrates what’s working and what’s not, sales leaders can easily tweak their processes and make meaningful workflow improvements. 

Increase visibility

True visibility across the entire revenue cycle is required for eliminating guesswork from your forecast. Unlike traditional forecasting processes (whose roll-up methods destroy data fidelity), robust AI revenue workflow platforms provide complete transparency into the success indicators of every active opportunity, and signal exactly where sellers should take action.

Ease of use and user interface  

The most powerful sales intelligence tool is only as good as its adoption rate. An intuitive interface can transform your sales process, while a complex one risks becoming unused. Prioritize solutions with clean layouts, customizable dashboards, and quick access to relevant information. 

Many teams struggle with systems requiring extensive training, leading to poor adoption. Involve your sales reps in testing different options - their input is valuable.

Guide growth

Using the insights from billions of sales activities, the right tool can boost revenue and scalability. It automates proven workflows to seamlessly guide every rep on every step in every stage of the revenue cycle, which facilitates faster growth. 

And by combining total visibility with AI, these systems help sales understand and act on their levers for growth, manage risk, and achieve stronger operational excellence.

Pricing and customer support

Different pricing models, from per-user to tiered plans, can significantly impact your total cost. Be wary of hidden fees or charges for essential features. 

The quality of customer support and training is also critical. Many organizations underestimate the importance of ongoing support, leading to underutilized features and frustrated users. Ask potential vendors about their support hours, response times, and training resources. 

Remember, a slightly pricier option with great support might offer better long-term value than a cheaper alternative with minimal assistance. 

The goal is to find a balance between cost-effectiveness and the support needed to maximize your investment.

Get a demo and test the platform 

Before committing to a sales intelligence platform, take advantage of free demos and trial periods. These hands-on experiences provide invaluable insights into how well the tool aligns with your specific needs. Many sales teams rush into decisions based on impressive feature lists, only to find the platform doesn't fit their workflow. 

During your demo, involve key team members and test real-world scenarios. Pay attention to the platform's responsiveness, data accuracy, and how easily it integrates with your existing tools. 

Don't hesitate to ask tough questions about implementation, support, and customization options.

Who should use sales intelligence?

Sales intelligence isn't just for closers – it's a powerful asset for numerous roles across a sales organization. From frontline reps to strategic decision-makers, the insights provided by these tools can transform how teams operate and drive results. 

Sales managers

The best sales intelligence software gives sales managers a high-level view of their team's performance and pipeline health. They can use these insights to identify coaching opportunities, allocate resources more effectively, and make data-driven decisions to optimize sales strategies.

Sales development reps

For sales development teams, sales intelligence is a goldmine for identifying and prioritizing high-potential leads. It enables them to personalize their outreach with relevant insights, increasing response rates and setting more qualified meetings for account executives.

Lead generation specialists

Sales intelligence improves lead generation efforts by providing data to build highly targeted prospect lists. These tools help identify companies that match ideal customer profiles and show buying intent, enhancing lead quality. 

Revenue ops teams

Revenue operations teams leverage sales intelligence to streamline processes and enhance cross-functional alignment. They use these tools to identify bottlenecks in the sales process, optimize territory planning, and ensure that all revenue-generating teams are working with consistent, high-quality data. 

How AI is transforming sales intelligence

Artificial intelligence has fundamentally changed what sales intelligence can deliver. Rather than simply aggregating data, AI-powered platforms now analyze patterns, predict outcomes, and recommend specific actions.

From data collection to intelligent insights

Traditional sales intelligence required reps to interpret raw data and decide how to act. AI shifts this burden to the platform itself. Machine learning algorithms process millions of signals to surface the insights that matter most, ranked by their likely impact on revenue.

According to Gartner research, by 2027, approximately 95% of seller research workflows will begin with AI, a dramatic increase from less than 20% in 2024. This shift reflects growing confidence in AI's ability to handle prospecting tasks autonomously.

AI-powered prospecting and lead scoring

AI excels at identifying patterns that predict conversion likelihood. By analyzing historical wins and losses alongside prospect characteristics, AI models score leads with greater accuracy than rules-based systems. This helps reps focus on accounts with the highest probability of closing.

Outreach's AI Prospecting Agent automates research, identifies high-quality leads, and generates personalized outreach, transforming prospecting from a time-consuming chore into a streamlined workflow. In the Prospecting 2025 report, 100% of AI-powered SDR users reported time savings, with nearly 40% saving four to seven hours per week.

Predictive analytics and deal guidance

AI analyzes deal progression patterns to forecast outcomes and flag risks early. Rather than waiting for a deal to stall, AI-powered systems alert reps to warning signs and recommend corrective actions. This proactive guidance helps teams address problems before they derail opportunities.

The impact on performance is measurable. According to research from SuperAGI, teams that frequently use AI in their sales processes report up to a 76% increase in win rates, 78% shorter deal cycles, and a 70% increase in deal sizes.

Conversation intelligence

AI-powered conversation intelligence analyzes sales calls and meetings to extract insights automatically. These systems identify customer objections, competitive mentions, pricing discussions, and buying signals without requiring manual note-taking.

Beyond individual calls, conversation intelligence reveals patterns across your entire sales organization. Leaders can identify which talk tracks drive wins, where reps struggle with objections, and how top performers differentiate themselves.

The future of AI in sales intelligence

The evolution continues toward increasingly autonomous AI agents that can handle complex, multi-step workflows independently. These agents will research accounts, prioritize outreach, personalize messaging, and manage follow-up sequences with minimal human oversight.

However, the goal is not to replace human sellers. AI handles repetitive tasks and data processing so reps can focus on what they do best: building relationships and solving customer problems. The most successful organizations will be those that effectively combine AI capabilities with human judgment and empathy.

Use Outreach’s AI Revenue Workflow Platform to help every member of your team make smarter decisions, improve productivity, and achieve better outcomes across the entire customer lifecycle.

Additional sales intelligence FAQs

What's the difference between sales intelligence and business intelligence?

Business intelligence (BI) encompasses a wide range of data analytics across an entire organization, providing insights for strategic decision-making at all levels. Sales intelligence zeroes in on data specifically relevant to the sales process. While BI offers a broad view, sales intelligence delivers targeted, actionable insights that directly impact a sales team's performance.

What's the difference between CRM and sales intelligence?

CRM platforms manage existing customer relationships by storing interaction history, tracking deal stages, and organizing account records. Sales teams use CRMs to log activities and monitor pipeline progress. Sales intelligence platforms serve a different purpose: they automatically collect and analyze external data to discover new opportunities. 

While a CRM tracks what has already happened with known contacts, sales intelligence reveals what could happen next by monitoring buying signals, company changes, and market trends across accounts you may not have engaged with yet. The most effective sales organizations use both together, with sales intelligence feeding qualified prospects into the CRM where reps manage relationships through the sales cycle.

How often should sales intelligence data be updated?

Sales intelligence data should be refreshed as close to real-time as possible. The ideal frequency depends on the type of data. Contact information may require less frequent updates than rapidly changing intent data or technographic details.

Can sales intelligence replace traditional prospecting methods?

While sales intelligence significantly enhances prospecting, it doesn't entirely replace traditional methods. Instead, it complements and improves existing approaches. For instance, sales intelligence can help prioritize cold calls by identifying high-intent prospects. 

How does GDPR and other data privacy regulations affect sales intelligence practices?

GDPR and similar regulations like CCPA have significant implications for sales intelligence. These laws govern how personal data is collected, stored, and used, emphasizing consent and the right to be forgotten. Reputable sales intelligence platforms have adapted by implementing strict data compliance measures, obtaining proper consent, providing transparency about data usage, and offering data deletion options.

What are some common challenges in implementing a sales intelligence strategy?

Implementing a sales intelligence strategy can present several challenges, but with proper planning, these can be effectively addressed. Common challenges include data quality and accuracy, integration with existing tools, adoption and training, and cost considerations.

What is sales intelligence software?

Sales intelligence software is a category of tools designed to help sales teams gather, analyze, and leverage data to improve their sales processes and outcomes. These platforms automate the collection and processing of relevant information, providing sales professionals with actionable insights as they prospect and manage accounts.

Core capabilities include lead generation and enrichment, company profiling, intent data tracking, predictive analytics, CRM integration, competitive intelligence, real-time alerts, and territory mapping. Together, these features help teams identify high-potential prospects, personalize outreach, and improve overall sales efficiency.