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About Megan Morreale

Megan's expertise is data storytelling and thought leadership for companies in the advertising, sustainability, security, healthcare, CRM, HR tech and finance spaces. She regularly contributes to sites like Content Marketing Institute, SEMRush, Vox Media, and Instapage; and has ghost-written pieces for executives on sites like CNBC.com and The Independent.

How Marketing Teams Should Optimize Website for Conversions that Align with B2B Sales

You might have heard before that marketing and sales can sometimes experience the business version of a sibling rivalry, but it’s not quite what you think.

Within business-to-business (B2B) organizations, marketing’s focus is on generating leads, while sales focuses on getting those leads to close. A disconnect happens when your marketing team (with good intentions) focuses on volume over quality, therefore resulting in passing over a high volume of leads to sales that just won’t close.

In this article, we’ll walk through a framework for how to categorize leads that come in through your website, how to build website messaging and landing pages that are consistent and relevant for each type of category, and how to optimize for intent as you go.

A General Framework for Categorizing Website Leads

It might seem obvious that your marketing team should focus on quality over quantity, or ideally both at the same time, but in practice the two can get a bit muddled.

We recommend generally categorizing leads into three different buckets:

  • High volume, high intent. These leads should be sent to sales and prioritized.
  • High quality, Low intent. These leads should be sent to a nurture funnel where they continue to be educated and engaged.
  • Low quality. These should get filtered out altogether, or directed to a different offer.

Ultimately, we’re talking about being more efficient with  qualification by allowing your website to do a lot of the work for you.

This includes building consistent messaging for each lead category, building and presenting relevant landing pages for those people, and optimizing for intent as you go.

Create Messaging that’s Consistent and Relevant

In order to qualify each website visitor as a member of one of the lead categories above, you’ll need to be able to automatically consider two things before displaying website content:

  • How that person got to your website. The messaging on the page they visit should be consistent with the email, ad, social posts, blog post content, or search result that preceded it.
  • Their business demographic. Use marketing automation, CRM and / or 3rd party data to ensure that messaging is also relevant to their business size or industry. Focus on the industries and business sizes that have an expected value for your sales teams, and send all others into the low quality bucket.

One effective way to do so is to display case studies from relevant industry competitors, if you have them available. 

For example, if someone from Wells Fargo visits your fintech website, they’ll likely respond more positively to a landing page with logos or success stories from Chase or Bank of America then from Investopedia or Stripe. If that’s not in the cards for you, focus on business size first. Before showing a Wells Fargo visitor logos from a fintech startup, show a success story from Macy’s, Delta, or another enterprise business.

This example from Shopify that’s optimized to attract businesses in e-commerce fashion. The logos and success stories listed on the page include e-commerce fashion brands, like AdoreMe, Cee Cee’s Closet and Coco and Breezy, immediately signaling to other fashion e-commerce companies that Shopify’s solution might be a good fit for them.

This example from Shopify that’s optimized to attract businesses in e-commerce fashion.

FunnelEnvy offers reverse IP, or account matching, and real time data integration to help marketers surface insights that allow them to display industry-specific webpages like these.

We also help companies display pages based on other types of data, like funnel stage, company size, and more.

This example from a large call center showcases how experimenting with personalized offers on their website by buyer segment led to an increase in qualified leads. 

This example from a large call center showcases how experimenting with personalized offers on their website by buyer segment led to an increase in qualified leads.

In fact, MQLs increased by 10X between March and June of 2020.

Graph showing MQLs increased by 10X

Landing pages that set the right expectations

Your landing pages essentially start the sales process by presenting your products to people for the first time. For them to be effective, they need to accomplish two things:

  • Mimic your sales people. This should be true for every lead category. Once a person converts through your website and makes it to the stage where they speak to sales, they shouldn’t receive an entirely different message than what led them to convert in the first place.
  • Clearly communicate what each site visitor should expect next. This will change depending on the lead category. If your site visitor is categorized as “high quality, high intent” and on their way to talking to a sales person, tell them that. If they’re getting redirected to a different offer or getting more information sent to their inbox, tell them that instead. 

One common mistake we see companies make is sending leads to a discovery meeting with a sales development representative (SDR) after they register for a demo. They’re expecting to see the product, when in fact, they end up in a frustrating meeting where they’re asked a lot of questions, afterwards which the real demo is scheduled depending on how they’ve qualified.

One way to rectify this is to make the discovery process part of the inbound flow, like we do at FunnelEnvy.

Our quick questionnaire helps us to categorize site visitors that convert so that we can set expectations for what will happen next, once they’ve completed the form.

Take a moment to fill out this questionnaire

Here’s another example that qualifies leads using company size and sales strategy:

Example that qualifies leads using company size and sales strategy

Optimizing for intent as you go

You’ve created messaging for each lead category and set up your landing pages so that the right expectations are set. Now it’s time to take it a step further by putting in place a mechanism to filter out low-quality leads or show them a different offer.

If a website visitor that’s not a highly valuable lead for your sales team comes along, you’ll want to be able to identify them with data that reveals their business size, industry, title, or any other identifying signal that makes a difference for you.

If someone comes along that doesn’t fall into any of the buckets you’ve identified as high value, consider sending them to your self-service solution (if one exists) or including a message upfront that right now, you’re just not the right fit for one another.

While it might seem scary to direct some leads away from sales, it can actually improve your sales team’s productivity and have a positive impact on revenue.

Working with FunnelEnvy, one startup increased their monthly marketing qualified leads (MQLs) by 30%, and grew revenue from closed or won deals by 250% the following quarter. Here’s what that success looks look over time:

One startup increased their monthly marketing qualified leads (MQLs) by 30%

This success came from optimizing their website to align with their B2B sales strategy, and by only surfacing high quality leads to their sales teams that were ready to buy.

Bonus: treat your high quality leads like gold

Those leads that are high quality and have the appropriate purchase intent should be treated like gold. 

To ensure that your sales team is successful, make sure there’s an established service-level agreement (SLA) on when and how sales is following up on those leads. For example, Marketo’s sales team commits to a 24-hour SLA.

If a tight 24-hour turnaround isn’t in the cards for you, automate your follow-up process with marketing automation or your customer resource management (CRM) software.

End the infamous sibling rivalry

The infamous sibling rivalry amongst marketing and sales isn’t actually a sibling rivalry at all — in fact, it only exists when these teams try to help one another in the wrong way.

Your website can do most of the heavy lifting to close this gap and help to qualify leads that are sent to sales automatically. 

If you’re looking for a custom solution to help personalize your website content for leads of different types, FunnelEnvy can help — contact us.

Don’t Fear a Cookieless World, Instead Shore Up Your First-Party Data to Optimize Your Funnel

If you haven’t yet heard, the cookie is on the outs — much to the cookie monster’s chagrin. The death nell was sounded by Google’s announcement of Privacy Sandbox, which is basically their plan to create a set of privacy standards.

This plan includes improving how cookies are classified, clearing up the details behind each person’s cookie settings, and plans to aggressively block fingerprinting. A fingerprint is created by stitching together a bunch of tiny signals about a person to create a full profile, and since people can’t access or delete their fingerprint, Google’s basically going to make it impossible to create them.

All of these intentions add up to one pretty plausible result — third-party cookies (the type used to make fingerprints, and fuel activities like retargeting) won’t be around much longer.

There’s another type of cookie though that’s not going anywhere — the first-party cookie, which allows marketers to collect first-party data. Focusing on shoring up your first-party data will not only prepare you for the death of the third-party cookie, but result in a stronger marketing strategy overall, regardless of the third-party cookie’s fate.

In this article, we’ll talk about the difference between the first and third-party cookie, why the first-party data is more valuable anyway, and how to use it to optimize your demand generation funnel.

First-party cookies vs. third-party cookies

Before we get into exactly how and why you should focus on first-party data, let’s straighten out the two types of cookies:

  • A first-party cookie is created and stored by the website you’re visiting; the one in the address bar. If you’re a site owner, first-party cookies allow you to collect data like customer analytics, language settings, the user journey, and other information that can assist you in improving your customer experience on-site.
  • A third-party cookie is created by sites other than the one you’re currently visiting. These other sites own some of the content, like ads or images, that you see on the site you’re currently visiting, and can therefore collect information about you while you’re there.

For example, say you’re shoe shopping with popular retailer DSW. When you visit DSW.com and shop for boots, you might not purchase right away. During that first visit, the homepage looks like this:

dsw-website

The next time you visit their site, there’s a new section of the homepage that displays the shoes you clicked on during your last visit. DSW dropped a first-party cookie on their site in order to remember that you were interested in buying boots. They then used this information to personalize your experience the next time you visited their site.

dsw-personalized-shoes-first-party

During this second visit, you made a purchase and provided your email. Two days later, DSW sends you an email about an upcoming boot sale. That’s first-party data. DSW used a combination of first-party cookies and personally identifiable information (PII), namely your email address, in order to personalize your experience.

dsw-third-party

Third-party cookies are most often used to retarget you on sites other than DSW.com. Perhaps after shopping for boots, you head over to nytimes.com to read up on the news. As you’re reading an article, you see a Google-owned banner ad advertising the shoes you just looked at:

nytimes-dsw-retargeting-ad

A lot of data exchange went on behind the scenes for you to see this ad. First, DSW partnered with Google and started using Google Ad Manager to serve ads around the web. The New York Times also partnered with Google to display ads on their site, in order to monetize their content.

Google then dropped a third-party cookie on DSW’s site to collect data on your visit, and DSW retargeted you on nytimes.com in the hopes of capturing your attention, and bringing you back to your site.

These are the types of cookies that Google is looking to guard against, and they’re the ones that are likely to die in the coming year.

Your first-party is data more valuable than third-party data anyway

The thought that third-party cookies are on the way out has caused a bit of a panic among marketers, mostly because they’ll have to come up with new ways to retarget site visitors.

But the thing is, focusing on first-party data is way more lucrative than scaling retargeting campaigns based on third-party data. First off, you collected that data directly from a person, and you know it’s accurate. Second, because you collected that data while that person was visiting your site, you know they’re actually interested.

Let’s go back to our shoe example — which interaction with a potential consumer would you find more valuable — the one on your owned website, or the display ad impression they probably didn’t see?

We bet your answer is the former.

First-party data is more valuable because it’s the best indicator of buyer stage, and therefore intent. Someone visiting your website has a much higher intent to interact with your brand than that of someone who saw a display ad.

For demand generation marketers, buyers go through many stages in their journey, so it’s really important that the data you’re collecting on those buyers captures their intent at each stage.

FunnelEnvy combines first-party data insights and offers personalization in order to align the offers on your website to the intent the buyer has at the time they’re visiting. This way, you move them down the funnel every time they visit, leading to better conversion rates and ultimately more revenue.

Here’s an example from Fitch Solutions. They guide their clients in making clear-sighted decisions through data, research and analytics on the capital markets and the macroeconomic environment.

Like many B2B technology companies, they thought of their homepage as a type of welcome center where they introduced themselves to people getting to know them for the first time:

Fitch-solutions

But, also like many B2B technology companies, they saw a lot of returning traffic, which is often a result of having a longer buyer journey. A “welcome center” isn’t an optimal experience for someone you’ve already welcomed.

FunnelEnvy worked with Fitch Solutions to personalize their homepage experience for each visit, and for returning visitors, they surfaced a relevant offer in place of their welcome message:

fitch-solutions-personalized-site

This change resulted in a 55% increase in conversion on site. By doubling down on optimizing their website using first-party data, Fitch Solutions made a huge impact on their funnel.

Optimizing the demand gen funnel with first-party data

So, how do you get from collecting first party data to activating it with a personalized experience on-site? The biggest challenge for the demand generation marketer facing the death of the third-party cookie is that first-party data is often siloed away in places like your customer resource management (CRM) software, marketing automation and in website analytics. 

If you want to truly personalize an experience, you need to bring all of that data together for a holistic view of the consumer journey.

The effort is well worth it — in fact, 77% of B2B sales and marketing professionals believe that personalization builds better customer relationships.

But to get there, something needs to bring all of that siloed data together so that you can target accordingly by buyer stage. The FunnelEnvy Backstage platform brings together these data sources, website analytics and experience tools to create a unified customer profile.

If you have the data, you can get sophisticated with offer personalization. You can attribute different user experiences to revenue, target by buyer stage and scale revenue.

Here’s an example from TIBCO Jaspersoft. They had one static product page that contained multiple offers for different personas within the organization. 

TIBCO-jasper-solutions-site

When they tried to squeeze multiple offers on a single page, offers competed for attention and blended in, which put the onus on the user to determine which was right for them. 

We worked with them to target specific personas with a single offer, based on data they had stored in their marketing automation platform. Through testing variations that replaced the default experience with a single focused offer, we saw an almost 50% improvement in revenue per visitor.

Conclusion: the death of the cookie is nothing to lament

While the death of the third-party cookie will mean a shift in strategy, there is a huge silver lining — as it’s phased out, demand gen marketers can use the opportunity to shore up their first-party data strategies, which are likely to result in a much larger impact on their funnel.

We’ll see less focus on (admittedly crappy) ad buys and retargeting campaigns, and a larger focus on leveraging first-party data insights better at home.

If you’re stuck on where to start when it comes to shoring up your first-party data strategy, we can help. Apply now to get started.

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