Personalization Guide
The 2020 Edition

The Marketer's Guide to Website Personalization

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Chapter 2:

Personalization trends in 2020

Our personalization results are great — but they are not unique to Proof. They are part of a secret movement that the best B2B marketers have started to explore and implement across the World Wide Web.

The modern marketer knows the power of personalization in building delightful customer experiences. According to a 2018 study by Evergage, 98% of marketers cited that personalization helps advance customer relationships. Further, 87% of marketers reported a measurable lift from these efforts.

That’s huge. But the data doesn’t stop there. Check out these personalization statistics:

  • Personalization reduces acquisition costs as much as 50%, lifts revenues by 5-15%, and increases the efficiency of marketing spend by 10-30% (McKinsey & Company)
  • Increasing personalization across multiple channels can increase overall consumer spending up to 500% (E-tailing Group)
  • More than 85% of users expect and accept personalization as a part of their online retail experience (Marketo)
  • 77% of consumers have chosen, recommended or paid more for a brand that offers a personalized service or experience (Forester)
  • 87% of companies see a lift in key metrics (such as conversion rates, engagement rates, or average order value) when they employ personalization (VB Insights)

Why personalization has failed in the past

Despite an unwavering signal that marketers want personalization and that consumers enjoy the experiences created by personalization, there still exists a market gap.

Nearly 60% of marketers report that real-time personalization is a challenge to execute. And only 12% of marketers surveyed in the Evergage report cited earlier were “very” or “extremely” satisfied in their level of personalization. Why is that?

We believe there are 4 key reasons personalization has failed to meet the demands of modern-day B2B marketers:

1. Not enough data

In the past, there was a big problem facing marketers that wanted to personalize their funnels: data was simply not available from anonymous visitors.

In the rare case that an anonymous visitor was identified before submitting information on your site, data points were not accurately being collected and followed up upon, adding another logistical complexity to the mix.

When you recognize that 98% of B2B traffic is anonymous, you see how real of a problem this can be. More than 9 out of every 10 visitors arriving on a site weren’t providing information to personalize a page.

In B2B SaaS, an extremely competitive vertical and a category full of buyers that understand what is possible on a site, this became a big issue. They are a consumer more aware of what is capable on a site and demanding of high-caliber service.

While the problem of identifying anonymous traffic still exists, the situation has greatly improved for marketers in 2019. Today, with an email address or an IP address, you’re able to tap into a 3rd party data source API such as Clearbit or FullContact to pull information on your previously anonymous visitors. Then with a personalization solution like Proof Experiences, you can deploy real-time adjustments for your site’s visitors. When you start speaking to a customer’s exact needs, you’ll see higher conversion rates and improved satisfaction. Bingo!

2. Difficult to track customer journey

Over the past several years, in the off-chance that data on a visitor was collected and properly tracked, it was nearly impossible to monitor the journey a customer traversed across marketing channels and touchpoints. If you’d identified a visitor to your marketing site, it wasn’t necessarily true that you’d immediately know when they received an email or visited a landing page or read a blog post.

Without that information stored in a central repository, it was improbable if not impossible to personalize quickly and accurately.

While the difficulty of customer journey mapping still continues to plague the industry, customer-data infrastructure solutions such as Segment and Hull.io have emerged to fill a gap for B2B SaaS teams. Now data-driven marketers can rely on a single source of truth when tracking user and customer activity on a site.

And this opens the door for real-time personalization at scale.

3. Constraints in time, resources

The biggest practical bottleneck on personalization to date has been companies have not had the time or resources to deploy unique experiences on their websites. Only 52% of surveyed marketers cited having the resources to deploy personalization and a smaller percentage — 22% — had a dedicated team at their disposal to launch these changes.

When marketers do have both time and resources, most personalization engines remain complex. High learning curves, and non user-focused solutions have come to dominate personalization.

Marketers are used to intuitive, self-service tools and solutions from tasks like email marketing (Hubspot and ActiveCampaign) to support (Drift and Intercom) and product improvements (Hotjar and Appcues). These self-service tools quickly install on your site and allow marketers to get started immediately diving into the weeds.

Personalization, sadly, has not kept up with these market shifts. Proof Experiences changes that by eliminating the learning curve and bringing visual editing that you’re used to from other platforms.

4. Personalization and customization are conflated

Customization and personalization — while similar — are not the same thing. Customization is initiated by the user. For example, on your first login to Hulu, you’re presented with a screen to select the content that most interests you. It requires you as a user to take an active action and cognitively think about the question posed by a brand.

This is not personalization. It relies on the user for action, and it is not a delightful experience for the user.
personalization trends hulu
An example of customization disguised as personalization.

Personalization, on the other hand, is when a brand is able to change the content or experience without your active knowledge. This can be by learning what type of content you find interesting, tracking your activity across the web, and turning to 3rd party data solutions to unlock data about you. All these forces help to provide a more relevant and efficient web experience.

personalization trends hulu
An example of personalization by the brand — learning through your behavior.

In our example from earlier, Hulu customizes your experiences by learning about your interaction with the product. Without realizing it, every time you interact with a show, you are signaling to their recommendation engine about what type of content you find interesting. Then, when they combine that information with other information they collect on you from your signup (income, demographics, location, device-type) and from 3rd party sources, Hulu can deliver more relevant experiences.

When done well, you don’t notice that personalization is occurring.

In the early days of personalization, there was a conflation of customization and personalization. Both customization and personalization can (and should) help marketers reach their goals. But personalization is much more powerful and less demanding process. Part of the failure of many prior personalization software offerings is that the software is cleverly disguised customization software.

The MarTech 5000 & new personalize trends in 2020

personalization trends martech 5000
The MarTech 5000 (a tracker of all the MarTech businesses) now includes over 8000 tools.

Over the past several years, valuations have reached all time highs with more than 300 startups now valued at over $1 billion. And 2018 was a record year for VC, indicating that growth in the high-tech sector is only continuing.

The emergence of all these companies have been a widely beneficial thing for consumers — as they’ve profited from the proliferation of new technology and better products. And in the world of marketing, it’s completely changed the role of a digital marketer.

personalization trends martech 5000
Enormous growth as documented by the MarTech 5000.

In 2011, there were 150 Marketing Tech (MarTech) companies. Today, there are over 7000 tools for marketers to consider. And with that extreme growth comes great opportunity.

Marketers now have software to turn to for nearly every part of their role — from setting up landing pages to running paid ads and sending automated emails. This makes the day to day of a growth marketing role easier. Plus, it opens the door to a wide array of new opportunities.

A/B testing, Analytics, Data Management, and Personalization have all been unlocked. And they can be used to improve conversion rates and drive more revenue for a business. Plus, since most software tools on the MarTech 5000 can integrate with one other — there are more touchpoints than ever to collect information on users and deploy highly personalized experiences to those users.

All of these forces mentioned in this chapter have created an environment where personalization is easier than ever to implement because data is available and immediately accessible.

Today, you can collect information from Hubspot when a user downloads a guide like this one, then you can track conversations that occur with your sales team in Drift, and then you can see what pages a visitor finds interesting. Based on that, you can send API calls to Clearbit & MadKudo to enrich and score all the information you’re receiving from a visitor. Finally, you can use all of that information (from different sources) to identify properties from a visitor and adjust your site in real-time.

No more asking unnecessary questions in long-form fields, no more time wasted on low-value leads, and a more valuable experience for each & every visitor. Personalization is not just a trend, it's the direction the Internet has been waiting for — and it’s time for B2B SaaS to adapt to the new environment.

In the next chapter
, we’ll cover how to start thinking about data collection as you consider implementing personalization on your site.

Chapter 3:
How to think about data
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