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How to Deliver Consistently Great Service

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How to Deliver Consistently Great Service

The global Software-as-a-Service market will be valued at $307.3 Billion by 2026. With several SaaS companies fighting to leverage the huge market — competition in any niche is unavoidable. But, there is a direct correlation between poor customer service and a loss of 67% of users.

This means that standing out from the rest in such a highly competitive market requires you to deliver quality customer service consistently.

But how can your SaaS firm assure a hassle-free sales and customer retention equilibrium?

The answer is — SaaS customer support.

What is SaaS Customer Support

Customer support for SaaS includes any action taken to help users achieve their desired results while using the software. Ideally, it should overcome software challenges and simplify the same for users.

Customer support includes live chat, chatbot, email, user communities, leveraging customer service software like Hiver, providing phone call assistance, etc. It involves quickly addressing customer queries and helping them get the best out of your SaaS product.

Improving your customer service for SaaS requires you to strategize your activities in these key customer service channels that ultimately help enhance the customer experience.

Here are some tips to get you started in the right direction.

#1. Emphasize your self-service options

A report suggests that 81% of customers want self-service options while only 15% are highly satisfied with the current self-service options. You can tap in this area.

Self-service for SaaS would include creating an updated frequently asked questions (FAQ) page, a self-help knowledge base with how-to guides and videos,a website chatbot that answers basic queries, etc. Such resources help by shortening the turnaround time and providing faster resolution.

Leverage a comprehensive knowledge management system like Document360 that integrates with Google Analytics to help identify search terms your customers frequently use to get the information they need. Also, your support team can contribute with recurring queries, addressing any latest bug, etc., to collectively address those with self-service.

For instance, Vimeo’s help center on their website provides a precise structure to aid users in finding the information they need.

#2. Customer feedback to improve your product

A consistent customer support service helps the product development team to continually roll out new features and implement UI changes by providing immediate feedback. Top SaaS customer support service includes going beyond the binary answers on whether they like the product.

Instead, try getting the reasons for their dissatisfaction as that is the only way to improve aspects that don’t work. This involves sending emails, getting on a call, sending surveys, etc.

Collect quantitative data to identify your user’s most pressing requirements and issues by leveraging different feedback methods mentioned below:

  • Customer Effort Score (CES) after a customer support interaction
  • Customer Satisfaction Score (CSAT) during product use
  • Net Promoter Score (NPS) for users who have used your product for a while
  • Involve social media listening as a proactive feedback method

Another aspect to include in your SaaS customer support service includes being pervasive in connecting with your customers. This means offering multiple support channels.

#3. Multiple options for customer support

Your SaaS customers may find it difficult to reach you for fast, effective customer service. It may take a lot of time, especially for first-time users. For instance, if a new customer needs live chat support, they might need to go to the contact us page to find the live chat button.

Therefore, it is best to offer multiple options for customer support — reaching out from the product itself is one way. And, if customers are on a website, provide chat options for immediate assistance. If possible, offer direct calling options within business hours.

This example shows how Recurly shows a “Support” option within the software UI for customers to connect with the customer support team. A user simply needs to click, and they will have a list of available help channels at a single, convenient spot.

A customer may have a different expectation for how quickly they will hear back from you depending on the channel they use to contact you. For instance, they expect a faster response to a social media message than a support ticket or email.

This highlights the need to include self-service and omnichannel customer service into your SaaS’s customer support model. Use a frequently asked questions (FAQ) website, chatbot, or online knowledge base to divert some queries from your help desk crew if clients are dissatisfied with lengthy wait/response time.

#4. Offer your team with necessary tools

Your SaaS business may need a range of customer service technologies like chat, knowledge base, customer service, etc. When your business grows, you will be catering to a larger number of users, necessitating the need for robust customer service tools to drive efficiency.

In all, the tools will help support the team in the following ways:

  • Support agents can access and validate profiles for most customers to provide customized help.
  • An online resolution needs remote access to consumers’ devices. For this, they may need multiple screens to refer to the troubleshooting steps and perform the same at the customer’s end.
  • Users need faster resolution. Therefore, powerful systems coupled with smooth customer service software are necessary.
  • Access to social listening software can go a long way in providing timely service to customers.

Even when building a FAQ forum, the most basic form of customer service, you need tools — a knowledge management system and technical documentation software like Robohelp, MadCap Flare, etc.

Wrapping up

The best customer service takes care of users throughout the SaaS product’s lifecycle. Following the tips mentioned above can help deliver the same, compelling customers to keep renewing their subscription to your product.

Outstanding customer service in the SaaS space helps nurture relationships that increase customer satisfaction and brand loyalty, with customers promoting your product to others in their network.

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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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