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The Leading Characteristics of Review Writers, Review Readers, and Successful Owner Responses

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The Leading Characteristics of Review Writers, Review Readers, and Successful Owner Responses

The author’s views are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.

Common sense is a useful asset, and as it turns out, it’s a fairly reliable guide when it comes to navigating the big world of online local business reputation. However, for the very first time, thanks to the recent report, The Impact of Local Business Reviews on Consumer Behavior, I was able to test my intuition against original, hard data revealing the habits of real review readers, review writers, and successful owner responses.

I highly recommend reading the full survey analysis, but today, I want to distill that mass of data down into three simple descriptions that emerged through the considerable work of analysis. These three descriptions codify dominant traits, characteristics and behaviors. They are meant to help you envision both the public and practices in an approachable manner, with the proviso that some people and industries will certainly fall outside these norms. For the bulk of local businesses, however, it’s my hope that this synthesis enables you to form a useful mental picture of who and what you’re working with when it comes to growing and managing your reputation.

Review readers are:

Habituated, very trusting unless faced with obvious signals of spam or low quality, much more trusting of other customers than of brands, still highly reliant on real world WOM recommendations, eager for a substantial amount of recent sentiment including negative sentiment, extremely forgiving when problems are resolved, and just one step away from interacting directly with your brand.

The data:

  • Review reading is now a given; 96% of the working age public will read reviews this year to navigate their local landscape. 56% of review readers are highly active daily or weekly readers. Even less active review readers (31%) will turn to reviews monthly or multiple times per year to get local business information.

  • With 86% of consumers citing reviews as either the most important or somewhat important signal of whether a business can be trusted, reviews are the most influential sales copy review readers will encounter. In fact, only 11% of consumers say they trust what a business says about itself more than they trust what customers say. 83% of review readers trust reviews as much or more than they did 3 years ago.

  • When choosing between businesses, review readers evaluate the following elements in order of importance: star rating, text content, recency, overall number of reviews, and the presence of owner responses.

  • Review readers are not as demanding as you might think. Only 13% of review readers require a perfect 5-star rating in order to choose a business. In fact, 44% cite flawless ratings as suspicious. 85% will consider a business with an overall 3 to 4-star rating.

  • Review readers’ trust can be lost at a glance. When a local business reviews itself or has suspect profiles reviewing it, or when its star rating or review count is notably low compared to competitors’, trust is eroded and review readers may look elsewhere.

  • Reviews exist on platforms over which businesses have only partial control, but a review readers’ next step lands them back in the brand’s own ball court most of the time, with a combined 91% of readers ending up on the website, at the place of business, or contacting the business directly as their next step. In other words, reviews have added to, but not replaced, traditional shopping behaviors.

Review writers are:

Civic-minded, appreciative, often self-motivated but more frequently in need of prompting, prone to forget to write when they are busy, highly likely to review you if asked via email, text, or face-to-face, active on multiple review platforms, deeply offended by rude service, bad products and incorrect online local business information, very willing to update what they’ve written and give a business a second chance when a complaint is resolved, and a key source of both sales and quality control.

The data:

  • Writing reviews is already a way of life for 41% of your customers who write reviews on a daily, weekly or monthly basis. An additional 44% who will write reviews several times a year may need to be asked, prompted and reminded.

  • Review writers say 65% of the negative reviews they write stem from bad/rude customer service. 63% cite a bad product, 52% cite false or incorrect online business info on assets like local business listings, 38% cite low-quality work on a job, 28% cite the failure of the business to resolve complaints in-person, and 28% cite inadequate safety protocols.

  • 73% of review writers are civic-minded, leaving sentiment to benefit their community, 63% write to express appreciation to local businesses, and 38% write to tell a local business that it needs to improve.

  • 39% of review writers haven’t been directly asked to write a review in the past 5 years. If asked, 85% will always, usually or at least sometimes write a review. Just 4% never write reviews in response to requests.

  • 54% of review writers like to be approached via email, 45% prefer person-to-person, and 29% prefer texting.

  • 38% of review writers simply forget to review your business when they have free time. 30% find the review writing process too confusing, 26% don’t believe the business will care enough to read what is written, and 19% are not being directly asked to write a review.

Successful owner responses should:

Happen within a two-hour to two-day time frame to please most reviewers, resolve stated complaints, avoid any type of acrimony, offer thanks for positive feedback and apologies for negative experiences, and be written with exceptional care because they influence 90% of customers to a moderate or extreme degree.

The data:

  • 60% of customers expect a response to their review within 2 days or less; 11% expect a response within 2 hours, 21% expect a response within 24 hours, and 28% expect a response within 48 hours; 24% say they expect a reply within a week.

  • 54% of customers will definitely avoid a business that is failing to provide a solution to a problem, 46% will definitely avoid a business with an owner who argues with customers in reviews, 47% of consumers will definitely avoid the business when an owner response offers no apology.

  • 67% of negative reviewers had an improved opinion of a brand when the owner responded well. 62% of negative reviewers would give a business a second chance after an owner response solves their problem. 63% of consumers will update their negative review or low-star rating once an owner response resolves their complaint.

In conclusion

Any local business which is founded on a customer-centric and employee-centric model already has a built-in advantage when it comes to managing the offline experiences that form the online brand narrative. Shoppers and staff simply want to be treated fairly and well. Local companies that meet these criteria in-store are capable of utilizing the same skills online, where digital sentiment has become like the front porch on a general store – a meeting, greeting, and helping spot for the community.

Local business owners and their marketers may need to invest in a few new tools to hang out on that porch effectively – think of them as the awning or wood stove you install to facilitate maximum comfort for everybody. But the skills that bring these tools to life are the ones the best local entrepreneurs already know – respect, attentiveness, accountability, empathy, responsiveness. Now we have the data to prove that the common sense approach of treating everyone well is actually very good business.

Hungry for more review data? Read: The Impact of Local Business Reviews on Consumer Behavior.

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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

Introduction

With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.

Types of YouTube Ads

Video Ads

  • Description: These play before, during, or after a YouTube video on computers or mobile devices.
  • Types:
    • In-stream ads: Can be skippable or non-skippable.
    • Bumper ads: Non-skippable, short ads that play before, during, or after a video.

Display Ads

  • Description: These appear in different spots on YouTube and usually use text or static images.
  • Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).

Companion Banners

  • Description: Appears to the right of the YouTube player on desktop.
  • Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.

In-feed Ads

  • Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.

Outstream Ads

  • Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.

Masthead Ads

  • Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.

YouTube Ad Specs by Type

Skippable In-stream Video Ads

  • Placement: Before, during, or after a YouTube video.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
    • Action: 15-20 seconds

Non-skippable In-stream Video Ads

  • Description: Must be watched completely before the main video.
  • Length: 15 seconds (or 20 seconds in certain markets).
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1

Bumper Ads

  • Length: Maximum 6 seconds.
  • File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
  • Resolution:
    • Horizontal: 640 x 360px
    • Vertical: 480 x 360px

In-feed Ads

  • Description: Show alongside YouTube content, like search results or the Home feed.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
  • Headline/Description:
    • Headline: Up to 2 lines, 40 characters per line
    • Description: Up to 2 lines, 35 characters per line

Display Ads

  • Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
  • Image Size: 300×60 pixels.
  • File Type: GIF, JPG, PNG.
  • File Size: Max 150KB.
  • Max Animation Length: 30 seconds.

Outstream Ads

  • Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
  • Logo Specs:
    • Square: 1:1 (200 x 200px).
    • File Type: JPG, GIF, PNG.
    • Max Size: 200KB.

Masthead Ads

  • Description: High-visibility ads at the top of the YouTube homepage.
  • Resolution: 1920 x 1080 or higher.
  • File Type: JPG or PNG (without transparency).

Conclusion

YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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A deeper dive into data, personalization and Copilots

Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.

To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.

Dig deeper: Salesforce piles on the Einstein Copilots

Salesforce’s evolving architecture

It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?

“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”

Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”

That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.

“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.

Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”

Let’s learn more about Einstein Copilot

“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.

For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”

Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”

It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”

What’s new about Einstein Personalization

Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?

“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”

Finally, trust

One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.

“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”

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