MARKETING
What is Conversation Intelligence and Facts you didnt know About the Software?
Before we get started with conversation intelligence, I want you to think about the most pressing challenges you face during a virtual sales meeting.
Take your time…did you get them?
Great.
The reason I made you do this exercise is simple. Unless you know where you struggle when virtually interacting with a client, it’s hard to understand the requirement of a software solution.
While virtually selling has engaged 80% of organizations, there’s no concrete evidence that all sellers have benefitted from the change. There are stories of struggle that we are unable to trace in all the hype of virtual selling.
According to HubSpot’s 2021 Sales Enablement Report, sales leaders who invested in remote sales noticed a return. The remote sellers who met or exceeded their revenue targets were 64 percent, while those who didn’t were just 50 percent.
But there’s definitely evidence that virtual selling can generate results better than pre-covid times if done correctly.
The more important question could be what is helping the sellers perform better remotely?
Out of the many agency tools available in the market, conversation intelligence is definitely one.
Today, we’ll discuss:
- What is conversation intelligence?
- Is Conversation Intelligence different than call recording software?
- How does Conversation Intelligence make use of AI and NLP to analyze conversations?
- Unusual facts about the conversation intelligence software
PS: If you’re familiar with conversation intelligence, skip to the good part- unusual facts about conversational intelligence.
What is conversation intelligence?
Conversation intelligence is a software platform that records calls(audio and video) between sellers and buyers. The data collected from these conversations are utilized to create data-driven insights.
The insights further assist sellers in performing better in the next call with the same prospect or another prospect.
Key features that a conversation intelligence possesses are;
- Record, transcribe and analyze calls
- Automate the note-making process
- Review and score call quality
- Review rep’s performance
- Design sales playbooks and run newspaper ads
- Integrating with sales tools like CRM software
CI tools are backed by artificial intelligence and constantly learning from sales conversations. The technology is designed to analyse speech as well as text.
Is conversation intelligence different than call recording software?
Yes, conversation intelligence is a more powerful tool than call recording.
The CI tool records the calls and analyzes calls to offer insights into the call intent, sentiment, follow-up requirements, email campaigns, next steps, and sales coaching.
A conversation intelligence tool offers post-call analysis to revenue-generating teams who wish to go one level up in engaging smartly with their prospects.
Intelligent conversations are not possible with call recording software. It doesn’t offer critical features like keyword analysis and moments to filter the call to extract specific parts of the calls.
Another essential element is to create a benchmark library with the help of the call recordings. Building the library helps sales coaching and ramp up the new hires faster.
So, to wrap up the context, conversation intelligence comprises call recording functionality, not the other way round.
How does Conversation Intelligence make use of AI and NLP to analyze conversations?
One study reveals that AI technology in sales allows employees to use their time efficiently, resulting in a 40% increase in total business productivity.
Conversation analytics uses conversations to provide meaningful insights. Conversation analytics extracts valuable data from the speech with the help of natural language processing (NLP). The data extracted is further allowed to “understand” speech while artificial intelligence (AI) pulls and structures the data. The algorithm works this way– to analyze speech, call recording and transcription are performed by the NLP. This helps the AI read, locate patterns, and categorize the data by participants.
Okay, now we can move on to our favorite part.
4 unusual facts about the conversation intelligence software
1. Marketers enhance video view time created using customer intelligence.
Carestack reported a 60% increase in view time of their marketing videos. Carestack used customer intelligence data and identified the most talked about pain points and use cases.
Carestack’s marketers were able to design marketing videos–with customer-centric topics– which were published online with Vidyard.
Marketers have been investing time in conversation intelligence but utilizing it only to derive market trends. The direct use of the marketing videos was a fresh ray of purpose.
2. Virtual events list of attendees improves with related and targeted discussion topics.
Another fantastic use of conversation intelligence was identified with the virtual events hosted by Carestack. The selected customer conversations and topics for the event were discovered from the call recordings and the feature dashboard. The discovery made by the marketing team turned the usual virtual events into successful events.
3. Invest in cross-functional collaboration and team-selling in remote teams.
Do you know why remote teams trust sales software tools like conversation intelligence to collaborate on virtual meetings?
In the form of transcription, call data can be shared and stored by sales teams that depend on customer calls.
Cross-team discussions are more effective and productive when they are recorded and analyzed. Furthermore, no team has to take responsibility for customer data or calls, and there is no problem accessing calls.
According to several customers, cross-functional collaborations reviews are streamlined and effortless with conversation intelligence.
4. Push call notes to CRM automatically.
We are in an era where pushing data manually to a CRM is a discussion of the past. CRM software doesn’t work in silos and automatically talks to other sales stack components.
Employees can now access the CRM details while taking notes during sales meetings directly into the CRM.
CRM software such as Pipedrive and Freshworks integrate conversation intelligence, dramatically reducing the notetaking effort and improving note quality.
For instance, look at the above image. Convin’s conversation intelligence tool pushes the completed call data to the Pipedrive account once the call is complete.
Here is what the completed call contains:
- Recorded call link
- Topics Discussed
- Action items/Next Steps
- Competitor discussed
- The overall customer sentiment:
We thought you should know just four items for today, but the list is still longer
Oh, wait!
Except for the unusual benefits of conversation intelligence, a few customers also reported specific benefits in sales meetings. Here’s what you may experience.
Bonus: We want to share six powerful reasons conversation intelligence is a must for virtual sales meetings:
- Enhancing Customer Relationships
- Removes Feature Bashing
- Faster and quicker notes
- Supports Mock Sales Meetings
- Brings Human Touch
- Builds Platform for Modern Buyers
Well, don’t wait for the right time to invest in sales software like conversation intelligence. Start experimenting with the software and evaluate your requirements.
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
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!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
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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