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When testing, look at the big picture

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When testing, look at the big picture

A common martech activity is testing different UI/UX (content, design, flow, etc.) elements in order to optimize some metric like lead form conversion rate.  While the actual responsibility for conducting such a test is usually assigned to a conversion rate optimizer, that doesn’t mean that other practitioners — regardless of whether they’re marketers, makers, modelers, or maestros — are not worth involving, since tests could have broad ramifications.

Indeed, A/B and multivariate testing typically have implications that reverberate throughout a martech stack — maybe beyond it.  In some cases that fact may present itself during the experiment phase, while in others the implications may pop up later on during an implementation phase.  That why it is important for martech practitioners to understand data flows.

Marketing and sales

The interaction between marketing and sales activities, is an example of a factor to consider.  Definitions for marketing qualified leads (MQL) and sales qualified leads (SQL), while related, differ for good reasons.  marketing and sales have different procedures, metrics, and goals.

For instance, a very common way people advocate to boost lead form conversion is to remove friction (in other words, fields).  In many cases, people are more likely to complete a form that requires less input and interaction than a form that requires a lot.  Simplifying a form could increase the quantity of leads while lowering the quality of leads.  What’s good MQL-wise is not necessarily beneficial from the perspective of SQL metrics.

Some of the “expendable” fields are likely for lead scoring.  They cause friction for marketing purposes, but they can help the sales team better understand a potential customer.  This enables salespeople to focus on targets who show strong intent to purchase, as well as tailor their efforts to the lead’s circumstances.

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So it’s entirely possible for an experiment variation that has fewer lead scoring fields to boost marketing conversions while inhibiting salespeople from closing deals.  Thus, when conducting such an experiment, it’s important to consider and monitor downstream metrics.

Multi-departmental considerations

Another factor to consider is how and when to collect required information.  This is important, since removing or moving data collection points in order to boost MQL or SQL metrics could likely have downstream ramifications — even after the sales process is completed.

For example, when selling insurance (health, dental, life, etc.) the final cost a policy will require knowing a lot of detailed and sensitive information about the person covered.  Does it make sense to ask for a lot of that information on an initial lead form, so that when a salesperson follows up they can give the prospect a price estimate with some certainty?  Or does it make sense to gather just some general information and allow the salesperson to provide a ballpark estimate along with how various factors will influence the cost?  There are pros and cons to both approaches, and each could be pursued depending on whether more total leads or more qualified leads are called for.

However, it’s important to know what information is ultimately required.  A prospect will have to provide all of it at some point to turn into a customer.  Thus, toggling between those collection options will require a bigger picture view.  If the decision is to remove a field from a lead form, when and where downstream will that information be collected?

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This may involve teams and systems that are outside of the martech stack, and therefore could require multi-departmental orchestration.  Then on top of that, if the decision is made to switch when certain information is collected, what happens to people who are in between the old and new collection points at the time of the switch?

Consider the big picture

It is crucial to consider the ramifications of common martech activities like conversion testing.  That perspective will help better ensure success.  For instance, there’s more to consider than MQL metrics, and at times, improved results with that one factor may come at a great cost down the line or in another crucial area.

As many practitioners can attest, sometimes changes are more complex than they may appear.  It’s really annoying to invest effort into finding a way to boost an upstream metric to only find that it will not work due to downstream issues.  Understanding data flows within and beyond the martech stack is one way to help mitigate against wasting time and effort on UI/UX testing that will ultimately not work out.

This story first appeared on MarTech Today.

https://martechtoday.com/when-testing-look-at-the-big-picture-248189


Opinions expressed in this article are those of the guest author and not necessarily Marketing Land. Staff authors are listed here.


Author:
Steve Petersen is a marketing technology manager at Western Governors University in Salt Lake City, Utah. He started on WGU’s marketing website team where he helped create and implement several initiatives including site redesign and maintenance, multivariate testing, user testing and mobile app development. 

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Google December Product Reviews Update Affects More Than English Language Sites? via @sejournal, @martinibuster

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Google’s Product Reviews update was announced to be rolling out to the English language. No mention was made as to if or when it would roll out to other languages. Mueller answered a question as to whether it is rolling out to other languages.

Google December 2021 Product Reviews Update

On December 1, 2021, Google announced on Twitter that a Product Review update would be rolling out that would focus on English language web pages.

The focus of the update was for improving the quality of reviews shown in Google search, specifically targeting review sites.

A Googler tweeted a description of the kinds of sites that would be targeted for demotion in the search rankings:

“Mainly relevant to sites that post articles reviewing products.

Think of sites like “best TVs under $200″.com.

Goal is to improve the quality and usefulness of reviews we show users.”

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Google also published a blog post with more guidance on the product review update that introduced two new best practices that Google’s algorithm would be looking for.

The first best practice was a requirement of evidence that a product was actually handled and reviewed.

The second best practice was to provide links to more than one place that a user could purchase the product.

The Twitter announcement stated that it was rolling out to English language websites. The blog post did not mention what languages it was rolling out to nor did the blog post specify that the product review update was limited to the English language.

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Google’s Mueller Thinking About Product Reviews Update

Screenshot of Google's John Mueller trying to recall if December Product Review Update affects more than the English language

Screenshot of Google's John Mueller trying to recall if December Product Review Update affects more than the English language

Product Review Update Targets More Languages?

The person asking the question was rightly under the impression that the product review update only affected English language search results.

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But he asserted that he was seeing search volatility in the German language that appears to be related to Google’s December 2021 Product Review Update.

This is his question:

“I was seeing some movements in German search as well.

So I was wondering if there could also be an effect on websites in other languages by this product reviews update… because we had lots of movement and volatility in the last weeks.

…My question is, is it possible that the product reviews update affects other sites as well?”

John Mueller answered:

“I don’t know… like other languages?

My assumption was this was global and and across all languages.

But I don’t know what we announced in the blog post specifically.

But usually we try to push the engineering team to make a decision on that so that we can document it properly in the blog post.

I don’t know if that happened with the product reviews update. I don’t recall the complete blog post.

But it’s… from my point of view it seems like something that we could be doing in multiple languages and wouldn’t be tied to English.

And even if it were English initially, it feels like something that is relevant across the board, and we should try to find ways to roll that out to other languages over time as well.

So I’m not particularly surprised that you see changes in Germany.

But I also don’t know what we actually announced with regards to the locations and languages that are involved.”

Does Product Reviews Update Affect More Languages?

While the tweeted announcement specified that the product reviews update was limited to the English language the official blog post did not mention any such limitations.

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Google’s John Mueller offered his opinion that the product reviews update is something that Google could do in multiple languages.

One must wonder if the tweet was meant to communicate that the update was rolling out first in English and subsequently to other languages.

It’s unclear if the product reviews update was rolled out globally to more languages. Hopefully Google will clarify this soon.

Citations

Google Blog Post About Product Reviews Update

Product reviews update and your site

Google’s New Product Reviews Guidelines

Write high quality product reviews

John Mueller Discusses If Product Reviews Update Is Global

Watch Mueller answer the question at the 14:00 Minute Mark

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Survey says: Amazon, Google more trusted with your personal data than Apple is

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survey-says:-amazon,-google-more-trusted-with-your-personal-data-than-apple-is-–-phonearena
 

MacRumors reveals that more people feel better with their personal data in the hands of Amazon and Google than Apple’s. Companies that the public really doesn’t trust when it comes to their personal data include Facebook, TikTok, and Instagram.

The survey asked over 1,000 internet users in the U.S. how much they trusted certain companies such as Facebook, TikTok, Instagram, WhatsApp, YouTube, Google, Microsoft, Apple, and Amazon to handle their user data and browsing activity responsibly.

Amazon and Google are considered by survey respondents to be more trustworthy than Apple

Those surveyed were asked whether they trusted these firms with their personal data “a great deal,” “a good amount,” “not much,” or “not at all.” Respondents could also answer that they had no opinion about a particular company. 18% of those polled said that they trust Apple “a great deal” which topped the 14% received by Google and Amazon.

However, 39% said that they trust Amazon  by “a good amount” with Google picking up 34% of the votes in that same category. Only 26% of those answering said that they trust Apple by “a good amount.” The first two responses, “a great deal” and “a good amount,” are considered positive replies for a company. “Not much” and “not at all” are considered negative responses.

By adding up the scores in the positive categories,

Apple tallied a score of 44% (18% said it trusted Apple with its personal data “a great deal” while 26% said it trusted Apple “a good amount”). But that placed the tech giant third after Amazon’s 53% and Google’s 48%. After Apple, Microsoft finished fourth with 43%, YouTube (which is owned by Google) was fifth with 35%, and Facebook was sixth at 20%.

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Rounding out the remainder of the nine firms in the survey, Instagram placed seventh with a positive score of 19%, WhatsApp was eighth with a score of 15%, and TikTok was last at 12%.

Looking at the scoring for the two negative responses (“not much,” or “not at all”), Facebook had a combined negative score of 72% making it the least trusted company in the survey. TikTok was next at 63% with Instagram following at 60%. WhatsApp and YouTube were both in the middle of the pact at 53% followed next by Google and Microsoft at 47% and 42% respectively. Apple and Amazon each had the lowest combined negative scores at 40% each.

74% of those surveyed called targeted online ads invasive

The survey also found that a whopping 82% of respondents found targeted online ads annoying and 74% called them invasive. Just 27% found such ads helpful. This response doesn’t exactly track the 62% of iOS users who have used Apple’s App Tracking Transparency feature to opt-out of being tracked while browsing websites and using apps. The tracking allows third-party firms to send users targeted ads online which is something that they cannot do to users who have opted out.

The 38% of iOS users who decided not to opt out of being tracked might have done so because they find it convenient to receive targeted ads about a certain product that they looked up online. But is ATT actually doing anything?

Marketing strategy consultant Eric Seufert said last summer, “Anyone opting out of tracking right now is basically having the same level of data collected as they were before. Apple hasn’t actually deterred the behavior that they have called out as being so reprehensible, so they are kind of complicit in it happening.”

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The Financial Times says that iPhone users are being lumped together by certain behaviors instead of unique ID numbers in order to send targeted ads. Facebook chief operating officer Sheryl Sandberg says that the company is working to rebuild its ad infrastructure “using more aggregate or anonymized data.”

Aggregated data is a collection of individual data that is used to create high-level data. Anonymized data is data that removes any information that can be used to identify the people in a group.

When consumers were asked how often do they think that their phones or other tech devices are listening in to them in ways that they didn’t agree to, 72% answered “very often” or “somewhat often.” 28% responded by saying “rarely” or “never.”

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Google’s John Mueller on Brand Mentions via @sejournal, @martinibuster

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Google’s John Mueller was asked if “brand mentions” helped with SEO and rankings. John Mueller explained, in detail, how brand mentions are not anything used at Google.

What’s A Brand Mention?

A brand mention is when one website mentions another website. There is an idea in the SEO community that when a website mentions another website’s domain name or URL that Google will see this and count it the same as a link.

Brand Mentions are also known as an implied link. Much was written about this ten years ago after a Google patent that mentions “implied links” surfaced.

There has never been a solid review of why the idea of “brand mentions” has nothing to do with this patent, but I’ll provide a shortened version later in this article.

John Mueller Discussing Brand Mentions

John Mueller Brand Mentions

John Mueller Brand Mentions

Do Brand Mentions Help With Rankings?

The person asking the question wanted to know about brand mentions for the purpose of ranking. The person asking the question has good reason to ask it because the idea of “brand mentions” has never been definitively reviewed.

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The person asked the question:

“Do brand mentions without a link help with SEO rankings?”

Google Does Not Use Brand Mentions

Google’s John Mueller answered that Google does not use the “brand mentions” for any link related purpose.

Mueller explained:

“From my point of view, I don’t think we use those at all for things like PageRank or understanding the link graph of a website.

And just a plain mention is sometimes kind of tricky to figure out anyway.”

That part about it being tricky is interesting.

He didn’t elaborate on why it’s tricky until later in the video where he says it’s hard to understand the subjective context of a website mentioning another website.

Brand Mentions Are Useful For Building Awareness

Mueller next says that brand mentions may be useful for helping to get the word out about a site, which is about building popularity.

Mueller continued:

“But it can be something that makes people aware of your brand, and from that point of view, could be something where indirectly you might have some kind of an effect from that in that they search for your brand and then …obviously, if they’re searching for your brand then hopefully they find you right away and then they can go to your website.

And if they like what they see there, then again, they can go off and recommend that to other people as well.”

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“Brand Mentions” Are Problematic

Later on at the 58 minute mark another person brings the topic back up and asks how Google could handle spam sites that are mentioning a brand in a negative way.

The person said that one can disavow links but one cannot disavow a “brand mention.”

Mueller agreed and said that’s one of things that makes brand mentions difficult to use for ranking purposes.

John Mueller explained:

“Kind of understanding the almost the subjective context of the mention is really hard.

Is it like a positive mention or a negative mention?

Is it a sarcastic positive mention or a sarcastic negative mention? How can you even tell?

And all of that, together with the fact that there are lots of spammy sites out there and sometimes they just spin content, sometimes they’re malicious with regards to the content that they create…

All of that, I think, makes it really hard to say we can just use that as the same as a link.

…It’s just, I think, too confusing to use as a clear signal.”

Where “Brand Mentions” Come From

The idea of “brand mentions” has bounced around for over ten years.

There were no research papers or patents to support it. “Brand mentions” is literally an idea that someone invented out of thin air.

However the “brand mention” idea took off in 2012 when a patent surfaced that seemed to confirm the idea of brand mentions.

There’s a whole long story to this so I’m just going to condense it.

There’s a patent from 2012 that was misinterpreted in several different ways because most people at the time, myself included, did not read the entire patent from beginning to end.

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The patent itself is about ranking web pages.

The structure of most Google patents consist of introductory paragraphs that discuss what the patent is about and those paragraphs are followed by pages of in-depth description of the details.

The introductory paragraphs that explain what it’s about states:

“Methods, systems, and apparatus, including computer programs… for ranking search results.”

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Pretty much nobody read that beginning part of the patent.

Everyone focused on a single paragraph in the middle of the patent (page 9 out of 16 pages).

In that paragraph there is a mention of something called “implied links.”

The word “implied” is only mentioned four times in the entire patent and all four times are contained within that single paragraph.

So when this patent was discovered, the SEO industry focused on that single paragraph as proof that Google uses brand mentions.

In order to understand what an “implied link” is, you have to scroll all the way back up to the opening paragraphs where the Google patent authors describe something called a “reference query” that is not a link but is nevertheless used for ranking purposes just like a link.

What Is A Reference Query?

A reference query is a search query that contains a reference to a URL or a domain name.

The patent states:

“A reference query for a particular group of resources can be a previously submitted search query that has been categorized as referring to a resource in the particular group of resources.”

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Elsewhere the patent provides a more specific explanation:

“A query can be classified as referring to a particular resource if the query includes a term that is recognized by the system as referring to the particular resource.

…search queries including the term “example.com” can be classified as referring to that home page.”

The summary of the patent, which comes at the beginning of the document, states that it’s about establishing which links to a website are independent and also counting reference queries and with that information creating a “modification factor” which is used to rank web pages.

“…determining, for each of the plurality of groups of resources, a respective count of reference queries; determining, for each of the plurality of groups of resources, a respective group-specific modification factor, wherein the group-specific modification factor for each group is based on the count of independent links and the count of reference queries for the group;”

The entire patent largely rests on those two very important factors, a count of independent inbound links and the count of reference queries. The phrases reference query and reference queries are used 39 times in the patent.

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As noted above, the reference query is used for ranking purposes like a link, but it’s not a link.

The patent states:

“An implied link is a reference to a target resource…”

It’s clear that in this patent, when it mentions the implied link, it’s talking about reference queries, which as explained above simply means when people search using keywords and the domain name of a website.

Idea of Brand Mentions Is False

The whole idea of “brand mentions” became a part of SEO belief systems because of how that patent was misinterpreted.

But now you have the facts and know why “brand mentions” is not real thing.

Plus John Mueller confirmed it.

“Brand mentions” is something completely random that someone in the SEO community invented out of thin air.

Citations

Ranking Search Results Patent

Watch John Mueller discuss “brand mentions” at 44:10 Minute Mark and the brand Mentions second part begins at the 58:12 minute mark

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