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14 Best Types of Charts and Graphs for Data Visualization [+ Guide]

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14 Best Types of Charts and Graphs for Data Visualization [+ Guide]

There are more types of charts and graphs than ever before because there’s more data. In fact, the volume of data in 2025 will be almost double the data we create, capture, copy, and consume today.

This makes data visualization essential for businesses. Different types of graphs and charts can help you:

  • Motivate your team to take action
  • Impress stakeholders with goal progress
  • Show your audience what you value as a business

Data visualization builds trust and can organize diverse teams around new initiatives. Let’s talk about the types of graphs and charts that you can use to grow your business.

Channels like social media or blogs have multiple sources of data and when you manage these complex content assets it can get overwhelming. What should you be tracking? What matters most? How do you visualize and analyze the data so you can extract insights and actionable information?

1. Identify your goals for presenting the data.

Do you want to convince or clarify a point? Are you trying to visualize data that helped you solve a problem, or are you trying to communicate a change that’s happening?

A chart or graph can help you compare different values, understand how different parts impact the whole, or analyze trends. Charts and graphs can also be useful for recognizing data that veers away from what you’re used to or help you see relationships between groups.

Clarify your goals, then use them to guide your chart selection.

2. Figure out what data you need to achieve your goal.

Different types of charts and graphs use different kinds of data. Graphs usually represent numerical data, while charts are a visual representation of data that may or may not use numbers.

So, while all graphs are a type of chart, not all charts are graphs. If you don’t already have the kind of data you need, you might need to spend some time putting your data together before building your chart.

3. Gather your data.

Most businesses collect numerical data regularly, but you may need to put in some extra time to collect the right data for your chart. Besides quantitative data tools that measure traffic, revenue, and other user data, you might need some qualitative data.

These are some other ways you can gather data for your data visualization:

  • Interviews
  • Quizzes and surveys
  • Customer reviews
  • Reviewing customer documents and records
  • Community boards

4. Select the right type of graph or chart.

Choosing the wrong visual aid or defaulting to the most common type of data visualization could cause confusion for your viewer or lead to mistaken data interpretation.

But a chart is only useful to you and your business if it communicates your point clearly and effectively.

To help find the right chart or graph type, ask yourself the questions below.

Then, take a look at 14 types of charts and graphs you can use to visualize your data and create your chart or graph.

Download the Excel templates mentioned in the video here.

5 Questions to Ask When Deciding Which Type of Chart to Use

1. Do you want to compare values?

Charts and graphs are perfect for comparing one or many value sets, and they can easily show the low and high values in the data sets. To create a comparison chart, use these types of graphs:

2. Do you want to show the composition of something?

Use this type of chart to show how individual parts make up the whole of something, like the device type used for mobile visitors to your website or total sales broken down by sales rep.

To show composition, use these charts:

3. Do you want to understand the distribution of your data?

Distribution charts help you to understand outliers, the normal tendency, and the range of information in your values.

Use these charts to show distribution:

4. Are you interested in analyzing trends in your data set?

If you want to know more information about how a data set performed during a specific time period, there are specific chart types that do extremely well.

You should choose a:

5. Do you want to better understand the relationship between value sets?

Relationship charts can show how one variable relates to one or many different variables. You could use this to show how something positively affects, has no effect, or negatively affects another variable.

When trying to establish the relationship between things, use these charts:

Featured Resource: The Marketer’s Guide to Data Visualization

Screen Shot 2020-04-09 at 3.09.44 PMDownload this free data visualization guide to learn which graphs to use in your marketing, presentations, or project — and how to use them effectively.

Different Types of Graphs and Charts for Presenting Data

To better understand each chart and graph type and how you can use them, here’s an overview of graph and chart types.

1. Bar Graph

A bar graph should be used to avoid clutter when one data label is long or if you have more than 10 items to compare.

Types of charts and graphs example: Bar chart - customers by role

Best Use Cases for These Types of Graphs:

Bar graphs can help you compare data between different groups or to track changes over time. Bar graphs are most useful when there are big changes or to show how one group compares against other groups.

The example above compares the number of customers by business role. It makes it easy to see that there is more than twice the number of customers per role for individual contributors than any other group.

A bar graph also makes it easy to see which group of data is highest or most common.

For example, at the start of the pandemic, online businesses saw a big jump in traffic. So, if you want to look at monthly traffic for an online business, a bar graph would make it easy to see that jump.

Other use cases for bar graphs include:

  • Product comparisons
  • Product usage
  • Category comparisons
  • Marketing traffic by month or year
  • Marketing conversions

Design Best Practices for Bar Graphs:

  • Use consistent colors throughout the chart, selecting accent colors to highlight meaningful data points or changes over time.
  • Use horizontal labels to improve readability.
  • Start the y-axis at 0 to appropriately reflect the values in your graph.

2. Column Chart

Use a column chart to show a comparison among different items, or to show a comparison of items over time. You could use this format to see the revenue per landing page or customers by close date.

Types of charts and graphs example: Column chart - customers by close date

Best Use Cases for This Type of Chart:

While column charts show information vertically, and bar graphs show data horizontally. While you can use both to display changes in data, column charts are best for negative data.

For example, warehouses often track the number of accidents that happen on the shop floor. When the number of incidents falls below the monthly average, a column chart can make that change easier to see in a presentation.

In the example above, this column chart measures the number of customers by close date. Column charts make it easy to see data changes over a period of time. This means that they have many use cases, including:

  • Customer survey data, like showing how many customers prefer a specific product or how much a customer uses a product each day.
  • Sales volume, like showing which services are the top sellers each month or the number of sales per week.
  • Profit and loss, showing where business investments are growing or falling.

Design Best Practices for Column Charts:

  • Use consistent colors throughout the chart, selecting accent colors to highlight meaningful data points or changes over time.
  • Use horizontal labels to improve readability.
  • Start the y-axis at 0 to appropriately reflect the values in your graph.

3. Line Graph

A line graph reveals trends or progress over time and you can use it to show many different categories of data. You should use it when you chart a continuous data set.

Types of graphs example: Line chart - avg days to close

Best Use Cases for These Types of Graphs:

Line graphs help users track changes over short and long periods of time. Because of this, these types of graphs are good for seeing small changes.

Line graphs can help you compare changes for more than one group over the same period. They’re also helpful for measuring how different groups relate to each other.

A business might use this type of graph to compare sales rates for different products or services over time.

These charts are also helpful for measuring service channel performance. For example, a line graph that tracks how many chats or emails your team responds to per month.

Design Best Practices for Line Graphs:

  • Use solid lines only.
  • Don’t plot more than four lines to avoid visual distractions.
  • Use the right height so the lines take up roughly 2/3 of the y-axis’ height.

4. Dual Axis Chart

A dual-axis chart allows you to plot data using two y-axes and a shared x-axis. It has three data sets. One is a continuous set of data and the other is better suited to grouping by category. Use this chart to visualize a correlation or the lack thereof between these three data sets.

Types of charts and graphs example: Dual axis chart - revenue by new customers

Best Use Cases for This Type of Chart:

A dual-axis chart makes it easy to see relationships between different data sets. They can also help with comparing trends.

For example, the chart above shows how many new customers this company brings in each month. It also shows how much revenue those customers are bringing the company.

This makes it simple to see the connection between the number of customers and increased revenue.

You can use dual-axis charts to compare:

  • Price and volume of your products
  • Revenue and units sold
  • Sales and profit margin
  • Individual sales performance

Design Best Practices for Dual Axis Charts:

  • Use the y-axis on the left side for the primary variable because brains are naturally inclined to look left first.
  • Use different graphing styles to illustrate the two data sets, as illustrated above.
  • Choose contrasting colors for the two data sets.

5. Area Chart

An area chart is basically a line chart, but the space between the x-axis and the line is filled with a color or pattern. It is useful for showing part-to-whole relations, like showing individual sales reps’ contributions to total sales for a year. It helps you analyze both overall and individual trend information.

Types of charts and graphs example: Area chart - users by lifecycle stage

Best Use Cases for These Types of Charts:

Area charts help show changes over time. They work best for big differences between data sets and also help visualize big trends.

For example, the chart above shows users by creation date and life cycle stage.

A line chart could show that there are more subscribers than marketing qualified leads. But this area chart emphasizes how much bigger the number of subscribers is than any other group.

These types of charts and graphs make the size of a group and how groups relate to each other more visually important than data changes over time.

Area graphs can help your business to:

  • Visualize which product categories or products within a category are most popular
  • Show key performance indicator (KPI) goals vs. outcomes
  • Spot and analyze industry trends

Design Best Practices for Area Charts:

  • Use transparent colors so information isn’t obscured in the background.
  • Don’t display more than four categories to avoid clutter.
  • Organize highly variable data at the top of the chart to make it easy to read.

6. Stacked Bar Chart

Use this chart to compare many different items and show the composition of each item you’re comparing.

Types of charts and graphs example: Stacked bar chart - mqls to sqls

Best Use Cases for These Types of Graphs:

These graphs are helpful when a group starts in one column and moves to another over time.

For example, the difference between a marketing qualified lead (MQL) and a sales qualified lead (SQL) is sometimes hard to see. The chart above helps stakeholders see these two lead types from a single point of view– when a lead changes from MQL to SQL.

Stacked bar charts are excellent for marketing. They make it simple to add a lot of data on a single chart or to make a point with limited space.

These types of graphs can show multiple takeaways, so they’re also super for quarterly meetings when you have a lot to say, but not always a lot of time to say it.

Stacked bar charts are also a smart option for planning or strategy meetings. This is because these charts can show a lot of information at once, but they also make it easy to focus on one stack at a time or move data as needed.

You can also use these charts to:

  • Show the frequency of survey responses
  • Identify outliers in historical data
  • Compare a part of a strategy to its performance as a whole

Design Best Practices for Stacked Bar Graphs:

  • Best used to illustrate part-to-whole relationships.
  • Use contrasting colors for greater clarity.
  • Make the chart scale large enough to view group sizes in relation to one another.

7. Mekko Chart

Also known as a Marimekko chart, this type of graph can compare values, measure each one’s composition, and show data distribution across each one.

It’s similar to a stacked bar, except the Mekko’s x-axis can capture another dimension of your values— instead of time progression, like column charts often do. In the graphic below, the x-axis compares each city to one another.

Types of charts and graphs example: Mekko chart - world's largest asset managers

Image Source

Best Use Cases for This Type of Chart:

You can use a Mekko chart to show growth, market share, or competitor analysis.

For example, the Mekko chart above shows the market share of asset managers grouped by location and the value of their assets. This chart makes it clear which firms manage the most assets in different areas.

It’s also easy to see which asset managers are largest and how they relate to each other.

Mekko charts can seem more complex than other types of charts and graphs. So, it’s best to use these in situations where you want to emphasize scale or differences between groups of data.

Other use cases for Mekko charts include:

  • Detailed profit and loss statements
  • Revenue by brand and region
  • Product profitability
  • Share of voice by industry or niche

Design Best Practices for Mekko Charts:

  • Vary your bar heights if the portion size is an important point of comparison.
  • Don’t include too many composite values within each bar. You might want to reevaluate your presentation if you have a lot of data.
  • Order your bars from left to right in such a way that exposes a relevant trend or message.

8. Pie Chart

A pie chart shows a static number and how categories represent part of a whole — the composition of something. A pie chart represents numbers in percentages, and the total sum of all segments needs to equal 100%.

Types of charts and graphs example: Pie chart - customers by role

Best Use Cases for This Type of Chart:

The image above shows another example of customers by role in the company.

The bar graph example shows you that there are more individual contributors than any other role. But this pie chart makes it clear that they make up over 50% of customer roles.

Pie charts make it easy to see a section in relation to the whole, so they are good for showing:

  • Customer personas in relation to all customers
  • Revenue from your most popular products or product types in relation to all product sales
  • Percent of total profit from different store locations

Design Best Practices for Pie Charts:

  • Don’t illustrate too many categories to ensure differentiation between slices.
  • Ensure that the slice values add up to 100%.
  • Order slices according to their size.

9. Scatter Plot Chart

A scatter plot or scattergram chart will show the relationship between two different variables or reveals distribution trends. Use this chart when there are many different data points, and you want to highlight similarities in the data set. This is useful when looking for outliers or for understanding the distribution of your data.

Types of charts and graphs example: Scatter plot chart - customer happiness by response time

Best Use Cases for These Types of Charts:

Scatter plots are helpful in situations where you have too much data to quickly see a pattern. They are best when you use them to show relationships between two large data sets.

In the example above, this chart shows how customer happiness relates to the time it takes for them to get a response.

Great use cases for this type of graph make it easy to see the comparison of two data sets. This might include:

  • Employment and manufacturing output
  • Retail sales and inflation
  • Visitor numbers and outdoor temperature
  • Sales growth and tax laws

Try to choose two data sets that already have a positive or negative relationship. That said, this type of graph can also make it easier to see data that falls outside of normal patterns.

Design Best Practices for Scatter Plots:

  • Include more variables, like different sizes, to incorporate more data.
  • Start the y-axis at 0 to represent data accurately.
  • If you use trend lines, only use a maximum of two to make your plot easy to understand.

10. Bubble Chart

A bubble chart is similar to a scatter plot in that it can show distribution or relationship. There is a third data set shown by the size of the bubble or circle.

Types of charts and graphs example: Bubble chart - hours spent online by age and gender

Best Use Cases for This Type of Chart:

In the example above, the number of hours spent online isn’t just compared to the age of the user, as it would be on a scatter plot chart.

Instead, you can also see how the gender of the user impacts time spent online.

This makes bubble charts useful for seeing the rise or fall of trends over time. It also lets you add another option when you’re trying to understand relationships between different segments or categories.

For example, if you want to launch a new product, this chart could help you quickly see the cost, risk, and value of your new product. This can help you focus your energies on a new product that is low risk with a high potential return.

You can also use bubble charts for:

  • Top sales by month and location
  • Customer satisfaction surveys
  • Store performance tracking
  • Marketing campaign reviews

Design Best Practices for Bubble Charts:

  • Scale bubbles according to area, not diameter.
  • Make sure labels are clear and visible.
  • Use circular shapes only.

11. Waterfall Chart

Use a waterfall chart to show how an initial value changes with intermediate values — either positive or negative — and results in a final value.

Use this chart to reveal the composition of a number. An example of this would be to showcase how overall company revenue is influenced by different departments and leads to a specific profit number.

Types of charts and graphs example: Waterfall chart

Image Source

Best Use Cases for This Type of Chart:

These types of charts and graphs make it easier to understand how internal and external factors impact a product or campaign as a whole.

In the example above the chart moves from the starting balance on the far left to the ending balance on the far right. Factors in the center include deposits, transfers in and out, and bank fees.

A waterfall chart offers a quick visual that makes complex processes and outcomes easier to see and troubleshoot. For example, SaaS companies often measure customer churn. This format can help visualize changes in new, current, and free trial users, or changes by user segment.

You may also want to try a waterfall chart to show:

  • Changes in revenue or profit over time
  • Inventory audits
  • Employee staffing reviews

Design Best Practices for Waterfall Charts:

  • Use contrasting colors to highlight differences in data sets.
  • Choose warm colors to indicate increases and cool colors to indicate decreases.

12. Funnel Chart

A funnel chart shows a series of steps and the completion rate for each step. Use this type of chart to track the sales process or the conversion rate across a series of pages or steps.

Types of charts and graphs example: Funnel chart - marketing funnel process

Best Use Cases for These Types of Charts:

The most common use case for a funnel chart is the marketing or sales funnel. But there are many other ways to use this versatile chart.

If you have at least four stages of sequential data, this chart can help you easily see what inputs or outputs impact the final results.

For example, a funnel chart can help you see how to improve your buyer journey or shopping cart workflow. This is because it can help pinpoint major drop-off points.

Other stellar options for these types of charts include:

  • Deal pipelines
  • Conversion and retention analysis
  • Bottlenecks in manufacturing and other multi-step processes
  • Marketing campaign performance
  • Website conversion tracking

Design Best Practices for Funnel Charts:

  • Scale the size of each section to accurately reflect the size of the data set.
  • Use contrasting colors or one color in gradated hues, from darkest to lightest as the size of the funnel decreases.

13. Bullet Graph

A bullet graph reveals progress toward a goal, compares this to another measure, and provides context in the form of a rating or performance.

Types of charts and graphs example: Bullet graph - new customers

Best Use Cases for These Types of Graphs:

In the example above, this bullet graph shows the number of new customers against a set customer goal. Bullet graphs are great for comparing performance against goals like this.

These types of graphs can also help teams assess possible roadblocks because you can analyze data in a tight visual display.

For example, you could create a series of bullet graphs measuring performance against benchmarks or use a single bullet graph to visualize these KPIs against their goals:

  • Revenue
  • Profit
  • Customer satisfaction
  • Average order size
  • New customers

Seeing this data at a glance and alongside each other can help teams make quick decisions.

Bullet graphs are one of the best ways to display year-over-year data analysis. You can also use bullet graphs to visualize:

  • Customer satisfaction scores
  • Product usage
  • Customer shopping habits
  • Social media usage by platform

Design Best Practices for Bullet Graphs:

  • Use contrasting colors to highlight how the data is progressing.
  • Use one color in different shades to gauge progress.

14. Heat Map

A heat map shows the relationship between two items and provides rating information, such as high to low or poor to excellent. This chart displays the rating information using varying colors or saturation.

Types of charts and graphs example: Heat map chart - highest degree vs. class identification

Best Use Cases for Heat Maps:

In the example above, the darker the shade of green shows where the majority of people agree.

With enough data, heat maps can make a viewpoint that might seem subjective more concrete. This makes it easier for a business to act on customer sentiment.

There are many uses for these types of charts and graphs. In fact, many tech companies use heat map tools to gauge user experience for apps, online tools, and website design.

Another common use for heat map graphs is location assessment. If you’re trying to find the right location for your new store, these maps can give you an idea of what the area is like in ways that a visit can’t communicate.

Heat maps can also help with spotting patterns, so they’re good for analyzing trends that change quickly, like ad conversions. They can also help with:

  • Competitor research
  • Customer sentiment
  • Sales outreach
  • Campaign impact
  • Customer demographics

Design Best Practices for Heat Map:

  • Use a basic and clear map outline to avoid distracting from the data.
  • Use a single color in varying shades to show changes in data.
  • Avoid using multiple patterns.

Put These New Types of Charts and Graphs Into Action

Now that you’ve chosen the best graph or chart for your project, try a data visualization resource that makes your point clear and visual.

Data visualization is just one part of great communication. To show your customers, employees, leadership, and investors that they’re important, keep making time to learn.

Editor’s note: This post was originally published in November 2020 and has been updated for comprehensiveness.

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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A deeper dive into data, personalization and Copilots

Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.

To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.

Dig deeper: Salesforce piles on the Einstein Copilots

Salesforce’s evolving architecture

It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?

“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”

Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”

That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.

“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.

Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”

Let’s learn more about Einstein Copilot

“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.

For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”

Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”

It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”

What’s new about Einstein Personalization

Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?

“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”

Finally, trust

One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.

“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”

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Why The Sales Team Hates Your Leads (And How To Fix It)

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Why The Sales Team Hates Your Leads (And How To Fix It)

Why The Sales Team Hates Your Leads And How To

You ask the head of marketing how the team is doing and get a giant thumbs up. 👍

“Our MQLs are up!”

“Website conversion rates are at an all-time high!”

“Email click rates have never been this good!”

But when you ask the head of sales the same question, you get the response that echoes across sales desks worldwide — the leads from marketing suck. 

If you’re in this boat, you’re not alone. The issue of “leads from marketing suck” is a common situation in most organizations. In a HubSpot survey, only 9.1% of salespeople said leads they received from marketing were of very high quality.

Why do sales teams hate marketing-generated leads? And how can marketers help their sales peers fall in love with their leads? 

Let’s dive into the answers to these questions. Then, I’ll give you my secret lead gen kung-fu to ensure your sales team loves their marketing leads. 

Marketers Must Take Ownership

“I’ve hit the lead goal. If sales can’t close them, it’s their problem.”

How many times have you heard one of your marketers say something like this? When your teams are heavily siloed, it’s not hard to see how they get to this mindset — after all, if your marketing metrics look strong, they’ve done their part, right?

Not necessarily. 

The job of a marketer is not to drive traffic or even leads. The job of the marketer is to create messaging and offers that lead to revenue. Marketing is not a 100-meter sprint — it’s a relay race. The marketing team runs the first leg and hands the baton to sales to sprint to the finish.

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via GIPHY

To make leads valuable beyond the vanity metric of watching your MQLs tick up, you need to segment and nurture them. Screen the leads to see if they meet the parameters of your ideal customer profile. If yes, nurture them to find out how close their intent is to a sale. Only then should you pass the leads to sales. 

Lead Quality Control is a Bitter Pill that Works

Tighter quality control might reduce your overall MQLs. Still, it will ensure only the relevant leads go to sales, which is a win for your team and your organization.

This shift will require a mindset shift for your marketing team: instead of living and dying by the sheer number of MQLs, you need to create a collaborative culture between sales and marketing. Reinforce that “strong” marketing metrics that result in poor leads going to sales aren’t really strong at all.  

When you foster this culture of collaboration and accountability, it will be easier for the marketing team to receive feedback from sales about lead quality without getting defensive. 

Remember, the sales team is only holding marketing accountable so the entire organization can achieve the right results. It’s not sales vs marketing — it’s sales and marketing working together to get a great result. Nothing more, nothing less. 

We’ve identified the problem and where we need to go. So, how you do you get there?

Fix #1: Focus On High ROI Marketing Activities First

What is more valuable to you:

  • One more blog post for a few more views? 
  • One great review that prospective buyers strongly relate to?

Hopefully, you’ll choose the latter. After all, talking to customers and getting a solid testimonial can help your sales team close leads today.  Current customers talking about their previous issues, the other solutions they tried, why they chose you, and the results you helped them achieve is marketing gold.

On the other hand, even the best blog content will take months to gain enough traction to impact your revenue.

Still, many marketers who say they want to prioritize customer reviews focus all their efforts on blog content and other “top of the funnel” (Awareness, Acquisition, and Activation) efforts. 

The bottom half of the growth marketing funnel (Retention, Reputation, and Revenue) often gets ignored, even though it’s where you’ll find some of the highest ROI activities.

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Most marketers know retaining a customer is easier than acquiring a new one. But knowing this and working with sales on retention and account expansion are two different things. 

When you start focusing on retention, upselling, and expansion, your entire organization will feel it, from sales to customer success. These happier customers will increase your average account value and drive awareness through strong word of mouth, giving you one heck of a win/win.

Winning the Retention, Reputation, and Referral game also helps feed your Awareness, Acquisition, and Activation activities:

  • Increasing customer retention means more dollars stay within your organization to help achieve revenue goals and fund lead gen initiatives.
  • A fully functioning referral system lowers your customer acquisition cost (CAC) because these leads are already warm coming in the door.
  • Case studies and reviews are powerful marketing assets for lead gen and nurture activities as they demonstrate how you’ve solved identical issues for other companies.

Remember that the bottom half of your marketing and sales funnel is just as important as the top half. After all, there’s no point pouring leads into a leaky funnel. Instead, you want to build a frictionless, powerful growth engine that brings in the right leads, nurtures them into customers, and then delights those customers to the point that they can’t help but rave about you.

So, build a strong foundation and start from the bottom up. You’ll find a better return on your investment. 

Fix #2: Join Sales Calls to Better Understand Your Target Audience

You can’t market well what you don’t know how to sell.

Your sales team speaks directly to customers, understands their pain points, and knows the language they use to talk about those pains. Your marketing team needs this information to craft the perfect marketing messaging your target audience will identify with.

When marketers join sales calls or speak to existing customers, they get firsthand introductions to these pain points. Often, marketers realize that customers’ pain points and reservations are very different from those they address in their messaging. 

Once you understand your ideal customers’ objections, anxieties, and pressing questions, you can create content and messaging to remove some of these reservations before the sales call. This effort removes a barrier for your sales team, resulting in more SQLs.

Fix #3: Create Collateral That Closes Deals

One-pagers, landing pages, PDFs, decks — sales collateral could be anything that helps increase the chance of closing a deal. Let me share an example from Lean Labs. 

Our webinar page has a CTA form that allows visitors to talk to our team. Instead of a simple “get in touch” form, we created a drop-down segmentation based on the user’s challenge and need. This step helps the reader feel seen, gives them hope that they’ll receive real value from the interaction, and provides unique content to users based on their selection.

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So, if they select I need help with crushing it on HubSpot, they’ll get a landing page with HubSpot-specific content (including a video) and a meeting scheduler. 

Speaking directly to your audience’s needs and pain points through these steps dramatically increases the chances of them booking a call. Why? Because instead of trusting that a generic “expert” will be able to help them with their highly specific problem, they can see through our content and our form design that Lean Labs can solve their most pressing pain point. 

Fix #4: Focus On Reviews and Create an Impact Loop

A lot of people think good marketing is expensive. You know what’s even more expensive? Bad marketing

To get the best ROI on your marketing efforts, you need to create a marketing machine that pays for itself. When you create this machine, you need to think about two loops: the growth loop and the impact loop.

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  • Growth loop — Awareness ➡ Acquisition ➡ Activation ➡ Revenue ➡ Awareness: This is where most marketers start. 
  • Impact loop — Results ➡ Reviews ➡ Retention ➡ Referrals ➡ Results: This is where great marketers start. 

Most marketers start with their growth loop and then hope that traction feeds into their impact loop. However, the reality is that starting with your impact loop is going to be far more likely to set your marketing engine up for success

Let me share a client story to show you what this looks like in real life.

Client Story: 4X Website Leads In A Single Quarter

We partnered with a health tech startup looking to grow their website leads. One way to grow website leads is to boost organic traffic, of course, but any organic play is going to take time. If you’re playing the SEO game alone, quadrupling conversions can take up to a year or longer.

But we did it in a single quarter. Here’s how.

We realized that the startup’s demos were converting lower than industry standards. A little more digging showed us why: our client was new enough to the market that the average person didn’t trust them enough yet to want to invest in checking out a demo. So, what did we do?

We prioritized the last part of the funnel: reputation.

We ran a 5-star reputation campaign to collect reviews. Once we had the reviews we needed, we showcased them at critical parts of the website and then made sure those same reviews were posted and shown on other third-party review platforms. 

Remember that reputation plays are vital, and they’re one of the plays startups often neglect at best and ignore at worst. What others say about your business is ten times more important than what you say about yourself

By providing customer validation at critical points in the buyer journey, we were able to 4X the website leads in a single quarter!

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So, when you talk to customers, always look for opportunities to drive review/referral conversations and use them in marketing collateral throughout the buyer journey. 

Fix #5: Launch Phantom Offers for Higher Quality Leads 

You may be reading this post thinking, okay, my lead magnets and offers might be way off the mark, but how will I get the budget to create a new one that might not even work?

It’s an age-old issue: marketing teams invest way too much time and resources into creating lead magnets that fail to generate quality leads

One way to improve your chances of success, remain nimble, and stay aligned with your audience without breaking the bank is to create phantom offers, i.e., gauge the audience interest in your lead magnet before you create them.

For example, if you want to create a “World Security Report” for Chief Security Officers, don’t do all the research and complete the report as Step One. Instead, tease the offer to your audience before you spend time making it. Put an offer on your site asking visitors to join the waitlist for this report. Then wait and see how that phantom offer converts. 

This is precisely what we did for a report by Allied Universal that ended up generating 80 conversions before its release.

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The best thing about a phantom offer is that it’s a win/win scenario: 

  • Best case: You get conversions even before you create your lead magnet.
  • Worst case: You save resources by not creating a lead magnet no one wants.  

Remember, You’re On The Same Team 

We’ve talked a lot about the reasons your marketing leads might suck. However, remember that it’s not all on marketers, either. At the end of the day, marketing and sales professionals are on the same team. They are not in competition with each other. They are allies working together toward a common goal. 

Smaller companies — or anyone under $10M in net new revenue — shouldn’t even separate sales and marketing into different departments. These teams need to be so in sync with one another that your best bet is to align them into a single growth team, one cohesive front with a single goal: profitable customer acquisition.

Interested in learning more about the growth marketing mindset? Check out the Lean Labs Growth Playbook that’s helped 25+ B2B SaaS marketing teams plan, budget, and accelerate growth.


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