What is Data-driven Marketing?

Data-driven marketing uses customer or prospect data to improve audience targeting, personalize communication, and increase customer engagement.

The data used in marketing can come from a variety of sources like online browsing activity, social interactions, or even surveys and conversations.

Today most marketing is already driven by data. However, how the data is used, and which data is used varies greatly across industries and teams, and is largely dependant on organizational goals.

Companies with a strong data-driven culture usually have a competitive advantage because it allows them to uncover opportunities that help them acquire customers faster, and create “made-for-you” customer experiences.

Being data-driven as a marketer is no longer an option – It’s the only option.

People looking at data
“Data are becoming the new raw material of business”
– Craig Mundie, former Microsoft Strategy Officer

6x

Companies who adopt data-driven marketing are 6x more likely to be profitable year-over-year.
– Forbes 

83%

Of marketers that exceeded their revenue goals in 2017 were using personalization
– Forbes

75%

Marketers that exceeded their revenue goals in 2017 were using personalization techniques 83% of the time
– Forbes

The Evolution of Marketing Data

Timeline of data driven marketing

Today, data is used across all departments in a company. From marketing to sales, support, accounting, and sometimes even all the way down to the lunch café.

But in the early days of the internet “data” wasn’t a big deal.

Nobody was collecting it like we do today, and data-abuse didn’t send businesses to court.

Website owners weren’t concerned about their rank in search engines or the bounce rate of their websites. Browsing activity wasn’t even something most knew they could use.

In fact, the very first seed of marketing data came around first in 1993.

Back then, most websites were built on HTML, static text and images.

Every time a visitor landed on a website, a request to download the website was sent to a server (and as a result, view its content), and each request was stored into a log file as a “hit”. This enabled website owners to see how many visitors they had.

But to understand these log files you had to be a developer or a member of the tech team.

90's Hit CounterIn 1996, the overly popular “hit counter” came along and as more and more people went online, website owners became obsessed by these hit counters.
Suddenly everyone could boast publicly with how many visitors their website had.

It was also around this time that eCommerce started taking off. Amazon opened with a bang in 1997, and shortly after people realized they could take their local shop online to instantly become a global business!

With the rise of eCommerce, marketers started using multiple channels in an effort to attract more customers to their online store, and they soon figured out they could send out email offers based on their customer’s previous purchases.

And so data-driven marketing was born.

It didn’t take long before building a contact database became best-practice for almost all businesses in every industry, and as soon as Salesforce released their cloud-based CRM, marketers gained access to more data they could ever dream of.

Google Analytics was released in 2005 and that enabled businesses to see where their visitors came from, spot trends, and use anonymous data to find business opportunities.

Data-driven Marketing: Everything you need to know

As web analytics evolved from tracking pageviews and clicks to measuring interest, intent, and defining segments… digital marketing transitioned from what once was almost an exclusively creative practice into one of the most important jobs in any company.

What type of data is important for marketers?

Almost all data is important, but not all data will be important to you or your company. Your organizational goals will help you decide what type of information you need to collect, what KPI’s to measure and how you use it in your marketing. 

In other words:

Don’t collect data just to collect data, make sure you actually use it. Not only will this save you from a lot of headaches down the road, but it will also save a lot of disk space as well.

Below you have the most common types of data used in marketing, ranked by their usefulness and how much data is available in that area.

Most useful type of data

In the bottom left corner () of the graph, there is mostly personal information. This is what we call “Hard Data”. 

It’s called hard because it’s very static, meaning it will probably never change during the time you’re in contact with your prospect or customer.

Even if the email address is absolutely necessary for you to be able to communicate with someone, you can’t use it for many other things than identifying your website visitors, enriching contacts with more data, pre-filling forms or sending out emails to your prospects.

However, as the bubbles grow larger and move up to the right () you can see that the most useful data is based on the user’s behavior and intent – not their personal information. 

Behavioral data is what we refer to as intent data or “Soft data”, and it’s called soft because it’s constantly changing. 

Hard data
Soft data

To understand how the soft data can be used in marketing, we have to know what kind of data we are talking about because there are multiple classifications based on where the data came from and how it was collected.

The different types of behavioral data are:

  • Anonymous 1st Party Data. These are people who visit your website and are typically only identifiable by their IP address. That IP address is then mapped to a company name if possible. Companies may use other solutions to help turn anonymous intent data into known intent data.
  • Known 1st Party Data. People that visit your website and are known by name. Maybe they filled out a form in the past or provided their contact information in another way. Once they have provided their information, you can then track their actions on your website and map that information to their company profile.
  • Anonymous 3rd Party Data. People that have visited another website that you do not own. There must be an indication that the data is relevant to your own products for it to be useful because it only contains IP information. This data is typically acquired through direct partnerships or vendors.
  • Known 3rd Party Data. People that have visited other websites and have also provided their information through a contact form. The website owner knows who they are, and you can acquire their data through a number of vendors.

But, you can’t just look at one type of data and ignore the other. The best way to approach a spreadsheet or dataset is to use your creativity and experience to come up with a big idea that speaks directly to your audience.

Personal information like an email address or a name is essential for basic communication but if you want to personalize the content and message, your marketing activities (ex. personalized email campaigns, retargeting ads, website widgets etc) need to adapt based on the user’s behavior and intent.

What does a successful data-driven team look like?

Contrary to popular belief, the success of a data-driven team does not rely on the amount of data they have. Instead, the success lies in the ability to use their collected data to create marketing campaigns.

recent study from NewVantage Partners shows that 85% of all companies are trying to be data-driven, but only 37% of that number say they’ve been successful.

Unfortunately, there’s often a large gap between desire and ability.

The gap of desire and ability

This gap is often due to differences in experiences, background, and knowledge amongst team members and managers. For example, if the senior management doesn’t understand the importance of using data in their decision-making process, the data you collect will end up on a hard drive collecting dust, and only a few persons knowing how to extract insights from it.

The best solution to this is to humanize the data and think of every click, page view, and opened emails, as something a person did.

If you want some real-life examples of how data is applied in marketing, check out our post 5 Real-World Examples of Data-Driven Marketing

Because the reality is that you are not selling anything to pageviews, and email addresses don’t take the subway to work. You’re selling to people, and it’s the person behind the click or submitted form that wants to buy from you.

To ensure that your team is successful in using data to make decisions, you need to view your data as the voice of your customer. This often means manually reaching out to customers, talking to them, and adjusting your marketing according to their feedback.

This is exactly how AirBnB started.

How Airbnb uses data to build a better company

Airbnb data science team

Back in 2009 when AirBnB got their first listings, Brian Chesky and Joe Gebbia (the two founders), believed that a key part of growing the company was to make their hosts fall in love with Airbnb.

They decided that the only way to do that was to visit their hosts personally and stay with them in their listed apartment.

Here’s a quote from one of Reid Hoffman’s articles explaining why this was a good choice:

As co-founder and CEO of Airbnb, Brian’s early work was more akin to a traveling salesman. He went door-to-door, meeting Airbnb hosts in person, taking photographs of their space, and learning what they did and didn’t like about his product.

This may sound inefficient if you’re an entrepreneur with global ambitions. But I’d argue that painstaking, handcrafted labor is actually the foundation of Brian’s success.“ – Reid Hoffman

AirBnB’s first pieces of actionable data were, literally, the voice of their customers. Sometimes, the best way to solve a problem is to not look at the data, but rather use data to verify your gut-feeling.

Of course, a lot has happened since then. Now data is a driving force in everything they do – from improving their product with A/B-tests to recruiting new team members.

But, what really makes Airbnb a successful data-driven company is a culture centered around data. All employees have access to and are empowered to make their decisions based on their own analyses and findings.

Here’s a quote from one of their blog posts on Medium:

We democratize data access to empower all employees to make data-informed decisions, give everybody the ability to use experiments to correctly measure the impact of their decisions, and turn insights on user preferences into products that improve the experience of using Airbnb

How Obama used data to win his presidential campaign

Obama campaign

In 2009, when Obama ran for president, he and his team used data-driven email marketing to ensure they consistently communicated to their voters, and to collect donations.

They mainly used two strategies to reach their goal.

  1. Segmentation
  2. A/B-testing

How Obama Used Segmentation To Increase Message Relevancy

In an effort to increase donations, Obama’s marketing team divided their audience into the following four segments:

  • Previous donors — The team sent a unique message to people who donated previously in the 2012 election. 
  • Quick donors — This was a subgroup of the previous segment. Quick donors saved their payment information and received quick-donation links in their emails. 
  • Non-donors — The team sent out personalized messages to the people who had never donated. 
  • Lapsed donors — The team personalized messages to people who had donated to the Obama campaign in 2008, but who had not yet donated in the current election. 

With these four target audiences defined, Obama’s team ensured that every email they sent was relevant to the recipient.

A critical skill of a data-driven marketer is the ability to test things. You know, experiment with different headlines, offers, images and doubling down on what works.

How Obama’s Team A/B-tested Their Way Into The White House

Obama and his team of almost 20 writers tested both subject lines and body copy almost every day of the campaign.

If you want to use A/B-testing in your marketing, you need to have a process to ensure you only test the most important things.

But luckily, it doesn’t have to be that complicated. Here’s the process Obama and his team used:

Obama’s A/B-Testing Process

Step 1: Write a bunch of emails

Step 2: Choose four to six and brainstorm

Step 3: Tailor the copy

Step 4: Test the message, then the subject line

Step 5: Go back to step 1

The team followed this procedure before they sent out every campaign, and it paid off big time. Below you’ll see a sample of all the headlines they tested.

Email subject lines used in obamas email campaigns

Their best performing email used the subject line “I will be outspent”, and generated over $2.6 million in donations.

Segmenting your email list and A/B-testing your subject lines are two of the most basic processes in data-driven marketing, and it’s definitely something you can do as well.

Even though both AirBnB and Obama’s team are huge data-driven operations they way they use their data is vastly different, yet they’re both still very successful.

“67% of marketers believe speed is one of the primary benefits of data-driven marketing, resulting in the ability to execute their campaigns quickly.”
– CMO.com

Why is data-driven marketing important?

Data-driven marketing is important because it enables companies to create individual experiences for individual customers, craft more relevant messaging, lower the cost of customer acquisition, and take more calculated risks.

You could say that the data answer your questions, without having to ask.

According to a 2017 study from Digital Doughnut, over 63% of surveyed marketers admitted they increased their spend on data-driven marketing from the year before (2016), and they spent over 20% of that budget on data-driven marketing campaigns.

Many of the fastest growing companies in the world have grown to where they are today because they know how to use their data better than their competitors.

Facebook and Google are two of these companies, and they make money by renting out data to businesses who want to advertise on their platforms.

However…

Building your business on “rented land” (social media and search engines) is dangerous because you don’t set the rules.

At any point in time, Facebook can cut the reach in half, Google can change their algorithms, increase advertising cost, or obliterate your rankings.

This is why marketers spend more money on data-driven initiatives and the reason behind why it’s becoming increasingly important to collect and control your own data.

But, using data is not only important for marketers. It’s important for your buyers as well.

Why it’s important for marketers:

✔ Lower marketing costs

✔ Better audience targeting

✔ Competitive advantage

✔ More effective up-, cross-, and down-selling

Why it’s important for consumers:

✔ Superior customer experience

✔ More relevant ads and communication

✔ “Made for you”-type products and services

✔ Personalized recommendations

If every ad you run would reach the perfect audience, 100% of the people who saw it would buy whatever you’re selling.

This kind of perfection will remain a dream for a long time, but the use of data can definitely bring you closer.

Example:

Let’s say you find out that LinkedIn is the source for 80% of your B2B leads, would you say it’s a safe bet to double-down on LinkedIn as your best lead source?

Knowing where most of your leads come from is just one part of the lead generation process, but it’s not enough to make a good decision and have the confidence to spend money on it.

What if you find out at a later stage that your LinkedIn leads never open any email campaigns you send them – what do you do?

The best thing you can do here is to go back to your original data and find out which source has the most engaged leads.

Email marketing is useless if your emails aren’t opened, and when looking closer you might find that leads coming from Google ads are the ones who open and click in your emails.

Would you still consider LinkedIn as your best source of new leads?

Quantity doesn’t directly translate to quality. So in this situation, you should optimize your Google Ads and try to maximize the results from that channel.

Being data-driven doesn’t necessarily mean you have to find all the insights at once in order to make a good decision.

Taking it step-by-step, going back to your original set of data every once in a while and adding more parameters helps you uncover valuable insight without getting overwhelmed.

Who is data-driven marketing for?

Data-driven marketing is for every company who wants to know their customers better, achieve more accurate targeting, and in general build a more effective marketing funnel.

It doesn’t matter if you’re a big company with 100+ teams, or a small local business with two employees – data can help you gain the competitive advantage you need.

The software has become cheaper and more user-friendly over the years, so getting access to actionable data is not as far-fetched as it may seem.

Every business has access to affordable tools that can show you who’s visiting your website, identify where your leads come from, and help you turn numbers into actionable tasks and real results.

In fact, you’re probably already more data-driven than you think.

  • If you’ve ever changed the creative or targeting of an ad based on poor results, you’ve made a data-driven decision.
  • If you’ve ever looked at a spreadsheet of contact records and found a pattern (most of my prospects are B2B!), you’ve have made a data-driven decision.
  • If you’ve ever run an A/B-test in some way, shape, or form, you have used data to improve results.

Almost every website you visit use some form of data-driven marketing. Whether they tailor the content based on where you click, or if they send out emails based on your past purchases or actions, it’s based on data.

However, there are a few industries in particular that are famous for using data to fuel their growth: 

Social Networks
Social networks like Facebook, Instagram, and Snapchat have a lot of users, and they know almost everything about them. With the help of AI and machine learning, they can discover hard-to-find growth opportunities and develop algorithms that help other businesses advertise on their platforms.

eCommerce
E-commerce giant Wish uses enormous amounts of data to display ads on Facebook. In 2015 alone, they spent over $100 million on Facebook ads according to Sensor Tower, making them the #1 advertiser on both Facebook and Instagram during that year. With millions of products available, they use algorithms that select products for their ads and also the target audience. E-commerce companies, in general, are very data-driven because it helps them lower their marketing costs. Most ecommerce businesses focus on creating content for their social media accounts.

SaaS (Software-as-a-Service)
Companies who are building marketing technology often use data-driven marketing to find new customers and personalize the onboarding for their customers. Since most marketing automation products are built for a specific audience, they use data to target audiences on Facebook, Google and through email marketing.

But it’s important to understand that for a small company it’s not about having unlimited amounts of data, but rather having a small amount of actionable and relevant data.

Examples of data-driven marketing activities

If you’ve ever seen or listened to a presentation from someone at Google, Facebook or Apple, you probably know they use data in ways most people could never imagine.

They’re the data-extremists. The only reason these companies are where they are today is that they are so skilled at putting their data to good use.

But for normal people like you and me, data-driven marketing doesn’t have to be this advanced to be useful.

In fact, there are tens of thousands of small businesses and solopreneurs using data in their marketing every day, and most of them didn’t graduate from Stanford with a PhD in computer science.

Below you’ll find a few examples of how businesses apply data-driven marketing in their everyday marketing activities.

Personalization

One of the most popular uses of data-driven marketing is definitely personalization.

According to a survey from Marketing Insider Group, 78% of U.S. internet users said personally relevant content from brands increases their purchase intent.

Earlier we talked about AirBnB’s humble beginnings. They focused on doing things that don’t scale, personally visiting every host who had a listing on their site.

Personalization doesn’t have to be scalable to be effective, and contrary to popular belief it doesn’t require a lot of data (at scale it does, but not when you’re starting out).

The easiest way to get started with personalization is by personalizing your email campaigns, sending out personal postcards or personalizing content on your website.

Below you’ll find three simple, but very powerful examples of how you can use personalization in your marketing (without breaking the bank):

Personal video

Personal video is one of the most powerful ways to reach out to prospects or clients. Compared to plain text emails, it hooks the recipient almost instantly and there’s a much higher chance that your message will come across.

In fact, attaching a video in an email leads to a 200-300% increase in click-through rates according to recent studies.

It’s most effective when used in the middle of the customer journey as a “nudging” tool, but it could also be used for cold outreach.

Most importantly, you can’t fake saying the other person’s name in a recording, and you literally make the video for them personally.

Even if this type of personalization can’t be automated and isn’t very scalable, it’s extremely powerful when done right.

Imagine you have 100 contacts in your database.

Let’s say 5/100 (5%) return regularly to your website to read your blog, show something to their colleagues, or for comparing you to another service.

If you can see who your website visitors are, you can do some manual lead scoring by Googling their company and looking at their activity profile from their visits to your website.

Perhaps you find that 3 out of 5 leads would be a great fit for your company, so you decide to send them a personal video.

personal video screenshot

A smart way of using video in this scenario would be to look at what pages they have visited on your website because this will give you an indication of what they’re interested in and what you should talk about in your video.

Pro tip: For an extra personal experience, record a 30 – 40-second video of your screen when you’re visiting their website and talk about how your company can solve their problems.  Use a service like Canned.me or Bonjoro to record your video and to send it in a regular email.

Personalized postcards

Would you be surprised if you received a postcard from a salesperson you talked to? Direct mail campaigns are usually considered a thing of the past, but the truth is they can be very effective just because of that very reason.

Personalized post card with firstname inserted

Mailchimp recently rolled out the ability to send postcards (by snail-mail) to the people in your email list. This makes it easy for you as a marketer to reach your customers outside of the inbox.

Since you have access to a lot of data in your email list, you could easily personalize what type of postcard you send out and to whom.

Our email inboxes are already filled to the brim with uninteresting mail, and almost nobody receives anything in their physical mailboxes, so receiving a postcard could be a very pleasant experience.

Postcard marketing should probably be used sparingly for special occasions, like as a thank-you note to seminar attendees or to give away an offer to your most loyal customers.

Website personalization

Personalizing the experience on your website can be tricky if you don’t know where to start. Depending if you’re in B2B or B2C, the type of personalization you want to use is a little different.

Personalization in B2B is mostly focused on delivering different types of content to prospects depending on where they are in the customer journey.

Personalization in B2C is mostly focused on recommending similar products (you know, like Amazon), sending out email offers based on previous purchases, and retargeting.

B2B Website personalization

But, no matter which industry you’re in, you need data for personalization to work.

More specifically, data in the form of browsing behavior (clicks, referral sources, interests).

You also need a tool that can help you actively use the data you collect. Google analytics won’t work, but Triggerbee is a tool that can help you act on the data you collect.

Personalization is probably the coolest form of data-driven marketing, but it’s also one of the most advanced. You can literally do almost anything, as long as you have data and developers to help you create the experiences.

Content Marketing

Writing content based on data is a surefire way to attract readers, leads, and shares.

However, the data you need to write good content is mostly collected from manual research.

This research process looks different for all companies, but here’s a basic example showing you how most companies collect their data and which tools they use:

Step 1: Finding topics to write about

It’s important that you know what other companies in your industry are talking about (or what they’re not talking about). This is important because you don’t want to write what everyone else is writing about, yet you don’t want to stray too far away from popular topics.

Buzzsumo is a tool that can help you find content that has a lot of engagement on social media.

Buzzsumo dashboard

This will give you an indication of whether the topic you’ve chosen resonates with your audience, and which social network has the potential to spread it.

After you’ve found a topic that seems popular, it’s time for step 2.

Step 2: Find out what people are searching for around your topic.

We’ll use Answerthepublic for this.

Search for any phrase or topic, and you will be presented with a list of questions that people regularly type into Google.

Search Queries surrounding your topic

This gives you a hint of which subtopics to include, and ensure you only answer questions people actually ask. 

Step 3: Write the content (and insert LSI Keywords)

Now you know what type of questions to answer and you know what type of headline works.

It’s time to start writing.

As you write, add some LSI Keywords from Google. The easiest way to find them is to search for your term in Google, and grab the suggestions that appear below the first 10 results:

List of related searches

Just make sure to insert them in a non-spammy way. If you can copy and paste these exact phrases, awesome. If not, rewrite them to fit your text.

Data-Driven SEO

If you want to be good at SEO, being data-driven is a must. 

However, the strategy is often neglected because it takes a long time before the effect kicks in. Count on not seeing any extreme bumps in traffic for at least 6 months. 

Landing pages often play a key role in how well your website ranks because nowadays Google wants you to cover topics, not just keywords. 

This means you have to create scalable landing pages that cover a topic very broadly, organizes specific types of content, and include more resources that are more in-depth. 

Here are a few examples: 

This strategy is more commonly known as creating “Pillar Content”. 

One company who have executed this strategy exceptionally well is Pinterest, and now their pin boards rank for millions of keywords.

You can read more about their data-driven SEO strategy in this blog post by Jeff Chang who is a technical growth lead at Pinterest.

Data-Driven Email Marketing

Email marketing is one of the most powerful marketing and sales channels out there, and there’s some really cool stuff you can do even with just a little bit of data.

Here are three examples of how marketers are using data to sell more with email marketing:

Becoming More Relevant With Segmentation

Email segments

When you’re using tools to segment your email list, you’re choosing a group of subscribers from your email list based on different traits, and write a specific piece of content to that group of people.

This ensures your content is relevant because not everyone on your list will be interested in the exact same thing.  

Unfortunately, most companies skip segmenting their lists because it takes time. But according to a study from Campaign Monitor, marketers have seen a 760% increase in revenue from segmented email campaigns – in other words, don’t skip your segmenting!

Re-sending campaigns to 2x open rates

Email campaigns resend

Another cool thing you can do is re-sending your campaign to subscribers who never even opened your first campaign. This little 5-minute hack can 2x your open rate if you’re lucky, and it’s all because of data.

Pro tip: When re-sending your campaign, make sure to include a “Re:” in your subject line along with a short “bumper content” at the top. Your bumper content should just be two-three lines of text explaining why you’re adding a “Re:” in your subject line. For example: “Hey, just wanted to make sure this didn’t get lost in your inbox – it’s some really important advice and thought you would like it.”

Action-triggered Emails

Triggered emails are also called transactional emails and it’s commonly used when onboarding new users for a product, when sending out receipts after a purchase, and when nurturing leads.

But, you can also use the browsing activity on your website to trigger emails.

Unlike regular email marketing, triggered emails don’t need segments to work. Instead, you need to set up rules.

For example, if you have two contact types in your list (company and private email addresses mixed) you can set up a rule to send out a specific email template only to subscribers who have performed a specific action on your website (i.e. clicked on a button, visited a certain page), and that doesn’t have “@gmail” or “@hotmail” in their email address.

Emails triggered by actions have 8x more opens and drives substantially more revenue than regular bulk emails (Experian).

Online Advertising

Almost everybody runs ads on Facebook, Google or LinkedIn. But most aren’t using the platforms to their fullest potential. 

These three companies know a lot about all of their users, and people in your audience are probably using at least one of these.

Here are a few ways you can use their data to boost results from your ads:

Facebook Lookalike Audiences

Facebook lookalike audience

A lookalike audience is a targeting audience Facebook can create for you based on a list of emails or website visitors.

This is incredibly powerful for all advertisers out there.

Let’s say you have an email list of 1000 people. You can upload your list of 1000 email addresses to Facebook, and let Facebook find people with the same traits as the people on your email list.

LinkedIn “ABM” Ads

IBM Linkedin ad

If you’re a B2B company, you have to be on LinkedIn. You don’t have to advertise, of course, but the platforms enable some really cool targeting options. 

Most of the users of LinkedIn are decision-makers, which makes it easy to find people who have the power to purchase your product or services. 

The best thing about advertising on LinkedIn is that you can target your ads to people with specific job titles. 

It’s very easy to reach executives in one specific company, so if your target audience is C-level execs…

…you could run one ad to your main target group and another ad to their colleagues. 

This ensures your ad reaches both the executive you want to reach, and the people they’re working with.

Google Ads

Google search ad from linkedin

Who do you ask when you’re looking for an answer?

Probably Google, right?

They pretty much know everything about anything and everyone, and if you run ads on their platform you will get access to all of their data.

But, it’s not as keyword-based as it once was. Even if you want your ads to appear in searches for “data-driven marketing”, your ads will show up in relevant searches like “how to create a data-driven strategy” and “data-driven companies”.

The reason for this is because Google displays search results and ads based on intent (i.e. what is this person really looking for?), and it’s all done automatically thanks to the massive amounts of data they have collected throughout the years.

If you want to get started, all you need to do is add a few relevant keywords, ensure your ads doesn’t show up for the wrong keywords (adding negative keywords), write some ad copy, manage your bidding, and iterate based on your results.   

Lead Generation

Every business needs an effective lead generation strategy.

But you can’t use strategies that worked 10 years ago because the behaviors and habits of your target audience have changed dramatically.

Today, your lead generation strategy needs to be data-driven.

With the right data, you can apply a few quick tweaks to your landing pages, forms, or ads and almost instantly see results. 

Here are a few examples of how data can help you boost your lead generation efforts:

Increased Conversion Rate

39.8% conversion rate

The conversion rate is a key indicator of how your lead generation strategy is performing. 

But in order to get a high conversion rate, you need two things:

  1. A great offer
  2. Great targeting

As long as you have the right offer, it will more or less sell itself. But if you are targeting the wrong audience… crickets. 

The data you already have about your current customers are most likely more than enough to boost your conversion rate by 10% – 50% in almost no-time. 

In fact, your current customer database is a goldmine of valuable information that can help you figure out your customer persona along with their goals, preferences, and challenges.

Just by knowing these things about your customers (goals, preferences, and challenges) will help you find out what to create for your potential customers. 

What’s more, if you can understand their behavior by collecting browsing activity you will become better at matching your offers with qualified leads.

Progressive Lead Profiling

Progressive lead profiling

Your website is one of the most valuable sales and marketing channels, and it’s unrivaled when it comes to converting visitors into leads. 

Up until now, the lead generation process has looked something like this:

  1. Drive traffic to the website
  2. Make visitors fill out a form (usually 5 – 6 form fields)
  3. An email sequence goes out
  4. Sales reach out

This is old-school.

A better way to generate leads is by using something called progressive profiling. This means you only ask your visitor to submit fewer pieces of information each time they visit your website, and only ask for the information you don’t have.

For example, the first time a visitor lands on your website you might only ask them for an email address. If they return to your website, you ask them for their website address and job title. The third time they visit, you might ask them to leave their phone number.

Doing it this way, you can avoid asking your visitors to fill out the same form over and over again, and ensure you only capture information your sales team need to close the deal.

Marketing Automation

Automated workflow

Marketing automation relies heavily on quality data. It’s important to ensure that the data the technology runs upon is accurate, valid, and relevant for the designated task.

If one or more contacts contains inaccurate or out-of-date data, your marketing automation service will quickly be rendered useless and undermine efforts to increase loyalty, engagement, and sales. 

But, having that said, it’s also one of the fastest ways to increase sales and lead engagement. 

For example, instead of trying to figure out which prospects have opened your emails and engaged with your posts on social media, your marketing automation software can most likely figure that out for you and create segments that you can use to take them further down your sales funnel. 

This will save hours each week for any company or marketer that wants to be more personal and relevant in their marketing. 

How to get started with Data-driven marketing

If you’ve gotten this far, congratulations. 

You’ve read about the benefits. You know who data-driven marketing is for. You know what data to collect… Now what?

It can’t be understated how important having the right tools, processes, and strategies in place are when you begin your journey into data-driven marketing. Without a clear idea of where you are heading, it’s too easy to get lost on the way.

You need clear goals:

  • What data will you be collecting?
  • What tools will you be using to collect that data?
  • How will this change processes for your current sales and marketing team?

These are important questions.

However, the best way to kickstart a data-driven initiative… Is to start with the data you already have. You just need to know what you’re working towards in order to know what to start with, and this starts with setting up goals. 

1. Set up clear goals

If you don’t know where you’re going, you’ll end up analyzing all data you have in every possible combination. 

This will hamstring you in your efforts to find valuable insights, so it’s important to set up good goals. 

Examples of bad goals: 

  • We need more visitors to our website so we can increase our sales
  • We want a higher email open rate
  • We need to rank higher in Google

Examples of good goals:

  • We need 20,000 visitors to our landing page about social selling, 500 leads and at least 20 customers in order to reach our quarterly revenue goal of $40,000.
  • We would like to generate 5 customers each month through email marketing. We might need to rethink what content we send out in order to be more relevant.
  • We need to rank in the top 10 of Google results in the topic of “Data-driven marketing” since we estimate it will bring our business in front of the right target audience.

Having clear goals plays a key role in the performance of your marketing activities, and the more specific it is, the easier it is for you to build out a plan of how to achieve it. 

For example, if you’d like to generate 5 customers each month through email marketing, start by looking at your open rate. If you have a low open rate, you need to improve your subject lines. Start by making it a habit to A/B-test your subject lines every time you send out an email campaign. 

Even if this is very basic, it’s one of the most effective ways of improving results for any marketing activity.

2. Search for solutions

When you know what goals to work towards, you need to evaluate if the services you already have is enough to achieve your goals.

For example, do you need to collect intent data in order to send out more relevant content in your email campaigns?

Then you need to look beyond Google Analytics, towards software like Triggerbee that tracks website activity from individual visitors, and update your contact list in your email marketing service.

Do your sales team need more insight about your website visitors in order to reach out to prospects more efficiently? Then you need to find a service that can identify companies and track their website activity. 

Your goals should be the main driver of your needs, and you should choose a solution that can help you achieve your goals.

3. Start Small… But Have Big Ambition

Jumping into the deep end of the pool before you know how to swim can prove to be a major mistake. 

Start with the data you already have, and make a few small decisions that put you on the track to reaching your goals. If you feel you need more data or different data, you can make a decision to purchase another system down the line.

The best advice we can give you is to find a process that works for you. Just like working out or meditating, using data is more of a habit than a skill. Reverse engineer your problems to make sure you’re looking for the right things. 

For example, if nobody is clicking on your links in your email campaigns, ensure that your subject lines are interesting enough. If nobody is converting on your landing page, ensure that your message is aligned with the audience you’re targeting. 

Resources and further reading