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How to fix the broken sales-marketing lead funnel

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How to fix the broken sales-marketing lead funnel

How to fix the broken sales marketing lead funnel

You’ve worked hard to turn the engagement from your recent marketing campaign into leads. Once your suspects have become prospects who’ve finally reached the scoring threshold, you toss the leads over the proverbial wall for sales to work. Later, you learn that after an initial push, your warm marketing leads have gone cold. This is because sales prioritized their list over the leads you sent to them. Moreover, sales doesn’t want you to do any marketing to their prioritized list because you lack the context of the relationships they are actively cultivating. This results in them not sharing data with you.

Misaligned goals. Poor execution due to a lack of communication. A dearth of shared, reliable data. All of it culminates in low trust between the two teams. It’s an illustration of the kind of scenario that can cause a deep divide between sales and marketing. And it impacts revenue.

So what do you do? Let’s take a look at how to fix the funnel.

According to Forrester, 94% of B2B purchasing decisions are made by buying groups and not individuals. Using a traditional Account-Based Marketing (ABM) approach these days is not enough. You have to go more granular to reach the right contacts. You have to go to the buying group.

Buying Group Marketing (BGM) focuses on engaging the key decision-makers inside your target accounts. This approach is about continually monitoring sentiment and engagement with buying groups within your target accounts to curate marketing and sales experiences accordingly. For instance, a finance buying group member likely has different concerns than an IT buying group member. Your content, creative, and delivery should be designed around that.

While traditional solutions have not been sophisticated enough to reliably identify and engage with buying groups, new technologies are emerging that measure probabilities of conversion for the group. Influ2’s Person-Based Advertising solution is a BGM enabler. Person-Based Advertising allows you not only to capture buyer engagement at an individual and buying group level. The score indicates how ripe the individuals are for outreach. This data can then be operationalized through the funnel and in existing workflows through platforms such as Salesforce, HubSpot, Marketo, and Outreach. This allows marketers to notify sales about the engagement activity of the contacts they care most about.

In the life of a lead, the Marketing Qualified Lead (MQL) is typically the link where ‘ownership’ passes from the hands of marketing into the hands of sales. Marketing and sales often work independently on either side of the MQL wall.

Marketing casts the content net wide into the sea of possible prospects. Sales goes narrow, addressing specific needs and hot buttons of individuals. When the lead is qualified by marketing, it passes from one world to the next—broad to narrow.

If the MQL is the main KPI you report on as a marketer, it’s not enough. Imagine a world where sales and marketing could work together throughout the entire life cycle of the lead—from initial awareness to closed deal. Getting rid of the MQL would unify the funnel into one holistic buyer’s journey where sales and marketing activities are not separate concepts but rather a well-coordinated effort targeting the entire buying group. It uses all the tools in the toolbox with surgical precision. A holistic effort such as this focuses on the buyer’s experience. A Buying Group Engagement score is a sales and marketing shared metric that could help to better align the teams and provide valuable insight to push the entire account across the finish line.

Our data shows that engaged buying groups get approximately a 2.5x boost in conversion rates on average versus non-engaged buying groups. Marketing that results in engagement at the sales development stage is priceless. In fact, one of our clients who targeted advertising at buying groups even deep in the funnel had great results. Buying groups that engaged with their advertising at the ‘demo stage’ had a 1.5x increase in conversion and at the ‘evaluation stage’ had a 2x increase in conversion.

This is a whole new way of working!

In many companies marketing and sales alignment begins and ends with a joint meeting to define an Ideal Customer Profile (ICP) so that teams target the right prospects. While BGM requires sales and marketing collaboration through the entire funnel, it’s also especially important messaging is aligned through each stage of the journey.

Without an MQL, the sales development team can prioritize the buying group engagement to hold warm conversations. But keep in mind that while priority goes to buying group engagement, any engagement with marketing effort is a sign of interest. If a target clicks on your ad, there is interest, so salespeople should be aware of every click.

At a high level, working together includes:

  • Aligning on strategy, covering areas such as buying group architecture and approaches, personas, personalization, and privacy.
  • Creating a relevant experience: from copy to creative from awareness to closed deals, handcrafting buyer experiences to reach prospects as individuals and not types.
  • Shared metrics: aligning marketing and sales metrics to end results and each other.

In the end, fixing the broken sales-marketing funnel will drive a different way of working.

It will require a much closer orchestration of activities through the funnel, one where everyone has a clear understanding and agreement about strategy, target audience, and the ideal customer profile. One where operationally, your systems are aligned to your strategy to keep the data flowing. You must define what types of data are critical to your business and what parts of the process you can automate. And you must have regular communication between sales and marketing teams to ensure that you carefully design and administer around the journey, putting the customer where they should be—in the center.

If you would like to learn more about how to implement a Buying Group Marketing strategy, please contact us.


About The Author

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Influ2 is a Person-Based Advertising platform for B2B companies that is purpose-built for B2B marketers who want to amplify their enterprise reach and revenue. It serves ads to specific decision-markers via display and social networks and provides sales with person-based and buying group insights that drive engagement within their target accounts. Where attention is finite, Influ2 helps you get in front of and drive engagement with people that want to engage with you. For more information, visit www.influ2.com.


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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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