3 Approaches To Scaling Conversion Optimization

Two powerful forces are crashing into each other in digital marketing — and conversion optimization is right in the middle. First: an ever-expanding explosion of digital touchpoints. Second: a wave of marketing technologies to address the challenges of scaling across those touchpoints.

There’s more than one approach to scaling conversion optimization in this environment, and they’re not mutually exclusive. We’ll examine three.

The Explosion Of Digital Touchpoints

The primary reason for this explosion of touchpoints is the continued migration of advertising dollars into online channels. eMarketer predicts that online ad spending worldwide will grow from 16.1% of total media budgets to 21.9% in 2015.

Given that worldwide advertising spend is expected to be $600 billion in 2015, we’re talking about tens of millions of additional dollars that will be invested online.

Driven by this influx of advertising dollars is an ever-expanding array of places to advertise. If we just limit ourselves to paid media, there’s the growing long-tail of AdWords search buys, an increasingly similar market for targeted display advertising, the rapid growth in Facebook PPC ads, the growing new space of mobile advertising, and so on.

In many cases, this isn’t just more real estate in which to run the same ads. Rather, it opens the door for a wider variety of ads that are tailored to their respective media and the contexts in which users see them.

These more targeted, context-specific ads then naturally have the opportunity to drive traffic to more targeted, context-specific landing pages. (Or, more broadly, post-click marketing experiences of many flavors.)

Testing Multi-Purpose Post-Click Experiences

One approach to dealing with this scale is to make sure your multi-purpose pages are well-optimized, given the variety of traffic that is sent to them.

This is the Google Website Optimizer approach. If you have a home page, or a small number of destination pages, you can run A/B and multivariate tests to find the most effect presentation on average for all users.

The upside of this approach is that you only have to invest optimization effort in a handful of pages. The downside is that you are trying to find the best “one size fits all” experience, and depending on how diverse your audience and traffic sources are, that may be a low common denominator.

For some types of experiences, such as shopping carts and e-commerce check-out processes — this works great. For other, more campaign-oriented or context-specific post-click experiences, this approach tends to hit a wall; it’s hard to serve different constituencies well with the same content and presentation.

There are some advanced technologies out there for optimizing different content on these multi-purposes pages for different audience segments.

In my opinion, however, that can be difficult for marketers to visualize at the campaign level. You no longer really have a shared experience that you can look at, understand, and propose tests and changes to. Instead, it’s more of a shell in which many different content combinations exist simultaneously in parallel universes.

There are powerful opportunities for that kind of personalization, which we’ll cover in a moment, but using it to drive the entire experience seems cool in theory, difficult in practice.

Optimizing Dedicated Landing Pages

A second approach is the “landing page optimization” school of conversion optimization. The essence of this approach is to create specific landing pages (or microsites or conversion paths) for different advertising campaigns and audience segments. You can then test and optimize each specific page, independent of the rest, for its particular audience.

This is probably the best understood approach — you can do a Google search to find hundreds of great articles on targeted marketing with landing pages. The challenge, however, is scaling up. What’s the cost efficiency for each additional landing page you create? How many different pages in total can you manage?

Luckily, those sort of operational challenges can be addressed with software tools that reduce the cost and time for producing new pages, as well as provide an organizational structure for managing a large collection of pages in total.

For instance, many marketing automation systems, such as Aprimo, Eloqua, Hubspot and Marketo, now include landing page features. Other vendors, such as Unbounce and ion interactive (disclosure: my own company), offer dedicated software solutions for this kind of post-click marketing.

However, even though these products streamline production and management of landing pages, marketers must still take responsibility for building out different pages for the different campaigns driving traffic.

This is both a feature and a challenge. It’s a feature because you can guarantee “message match” between the ads that inspire users to click and the experiences they receive after the click — you’re able to perfectly fulfill respondent expectations. It’s a challenge, because it doesn’t happen auto-magically; someone still needs to be guiding the creation of these experiences.

I liken this kind of rapid production post-click marketing to a blend of content marketing and conversion optimization.

Targeting Serendipitous Content & Offers

Finally, there’s a third approach that I touched on earlier — the use of personalization and algorithmic targeting software to dynamically populate specific offers or content elements to different respondents on a page. Although I expressed skepticism for using these technologies to generate the entire page, I think they can be very effective in populating certain pieces of the page.

The way I look at it, there are two types of relevancy in post-click marketing. The first is expected relevancy — when someone responds to a specific ad in a particular context, they expect the webpage that they arrive at to fulfill the promises implied or stated by that ad.

You can test different variations of presenting that expected content, but in all cases the content has to flow naturally and stay on message. In my opinion, that’s hard to do with a black box.

However, there is also room for serendipitous relevancy — where in addition to the main, expected message of a page, ancillary offers and content teasers can be presented around the primary content.

These secondary calls-to-action, cross-sell or upsell blocks, often placed in a sidebar, can afford to take guesses about what the user might like. If they’re wrong, there’s minimal penalty to the brand because the user wasn’t expecting serendipity.

However, if they happen to nail it — something that delightfully surprises the user (“I wasn’t expecting that!”) — it can drive significant lift to your conversion rate.

This kind of conversion optimization is prevalent in e-commerce, where store pages are often “fixed” and their primary content is deterministic, but there’s plenty of opportunity to dangle tantalizing hooks elsewhere on the page. Recommendations on Amazon are a classic example of this.

As I mentioned at the beginning, these different approaches aren’t mutually exclusive. You can employ one, two, or all three together. With more traffic headed your way, and a plethora of marketing technologies available for each of these approaches, your conversion optimization programs have a bright future ahead.