Interestingly, despite its favorable view, concerns still persisted around AI, with respondents indicating there are still unknowns about how the technology will be applied, which social media platforms are using it most effectively and whether it will result in more accurate targeting or reduced costs. Specifically, the report uncovered:

• 59% of participants saw AI as the greatest influence on the future of advertising;
• 56% of agencies and advertisers expected their budgets to increase in the next year;
• 48% of respondents said strengthening their national advertising is the top priority for 2024, followed by 26% whose top focus was improving local advertising; and
• 45% of professionals anticipated a change to their media mix because of third-party cookie deprecation.

More Advertising Spend Projected In 2024

After several lean post-pandemic years, most advertising and agency executives reported budget increases for 2024. Digital advertising is expected to constitute around two thirds of total ad spend among advertisers, while social media is the most desired allocation of spend for brand-focused advertising, with search engine marketing and social media tied with the lead for performance advertising.

Cookie Deprecation Only Draws Moderate Concern

With the end of third-party cookies looming, advertisers believe they are more prepared than previously anticipated. Many are already shifting to embrace first-party customer data strategies. Other emerging approaches include contextual and cohort-based targeting, machine-learning systems and CPC/CPA models.

“It’s no surprise AI has emerged as the key theme on advertisers’ minds in this study,” said Jackie Cutrone, CMO of NewtonX, in a statement. “We’ve harnessed the power of AI to gather and analyze this data, and along with our partners at Material, we’re committed to leveraging AI technology to provide business insights that help advertisers and brands navigate the challenges of 2024 and beyond.”

To learn more about the findings in the “The Digital Lead: 2024 Advertising Insights & Tech Trends Report,” check out the full report now.

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Created by senior marketing technology executives and leveraging machine learning, Audyence RTD analyzes more than 17.5 billion firmographic, behavioral and technographic data points to help reduce the operational and capital expenditures associated with planning, purchasing, selling and executing demand generation campaigns.

“The global B2B lead generation industry is already a $21 billion market growing more than 15% per year, but it’s still too dependent on manually managing campaigns and a troubling lack of transparency,” explained Audyence Co-founder and CEO Karl Van Buren in a statement. “That’s where Audyence RTD comes in. To buy leads before our solution, marketers had to work with five or six or more brokers, negotiate with each separately by email or phone call and then manually manage those separate campaigns. We’re automating that entire process from end to end for as many publishers as they want to work with through our marketplace, reducing agency labor costs by 20X.”

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AUDIENCE is designed to leverage a combination of job roles, functions, firmographics and specialized technology intelligence, such as past purchases and installs, through BlueWhale’s partnership with HG Insights to create highly customized campaigns. To help users rely on their existing advertising infrastructure, BlueWhale also invested in third-party audience integration tools. 

“Our tradition of and commitment to delivering tangible ROI for our demand generation customers is constant, reliable and very well-known,” said James Oberhausen, President and General Manager of BlueWhale Research, in a statement. “With the launch of AUDIENCE, we are delighted to offer more opportunities for our clients and agency partners to enjoy the dedicated service and positive outcomes that are characteristic of BlueWhale’s offerings. Digital advertising teams are a new focus for us in our customer base and agency partnerships. Our attention to this important and complex function in marketing and broader go-to-market organizations promises to deliver tremendous value for everyone in 2024 and beyond.”

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Specifically, the innovations include:

• Campaign Outcomes, which allows customers to pick their ideal campaign outcomes and then utilizes Demandbase’s Demand Side Platform (DSP) to optimize each impression and campaign strategy;
• Campaign Influence Metrics that reportedly make it easier to review B2B-specific influences, such as increases in website engagement, pipeline and revenue;
• Creative Library Enhancements that provide digital marketers with more control over their creative assets to create and launch native, video and connected TV campaigns within the campaign builder; and
• Job Level and Job Function Exclusions designed to prevent impressions from being served to people outside of the buying group, regardless of their intent level.

“While our expert teams will always be here to partner with customers on successful campaign strategy, we have also always had a significant AI component behind our DSP and are excited to offer more self-serve capabilities,” said Gareth Noonan, General Manager, Advertising at Demandbase, in a statement.

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Samba AI seeks to automatically and instantly recognize when a company’s logo appears on screen or a brand is mentioned during a program to offer comprehensive viewership analysis. The product also analyzes the surrounding sentiment of brands, helping provide companies with a detailed understanding of their portrayal throughout the programming. It’s also interoperable within Samba TV’s outcome-based measurement suite.

“Samba TV has been investing in research and development for generative AI and ML-based analysis of video for more than a decade,” said Ashwin Navin, CEO and Co-founder of Samba TV, in a statement. “We’re now taking our years of AI innovation a step further by working with some of the world’s most recognizable brands to transform the way media investments are evaluated. We are using our powerful first-party data to train best-in-class AI models to inform the most important decisions made by advertisers.”

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Quality Attention uses advanced machine learning technology, actionable data from Lumen Research’s eye-tracking technology and various other signals — such as viewability, ad situation and user interaction — to weigh them into a single attention score. IAS’s attention model is designed to provide a singular view of campaigns’ attention performance, based on a pool of data consisting of billions of impressions and millions of conversion events.

“Attention measurement must inform actions that drive superior results for advertisers,” said Yannis Dosios, Chief Commercial Officer for Integral Ad Science, in a statement. “Our Quality Attention offering is purpose-built to help brands and agencies navigate through media clutter to seamlessly understand how media visibility, the ad environment and customer interaction impact campaign performance. According to our research, brands that focus on driving higher IAS attention scores achieve up to a 130% lift in conversion rates leading to a better return on their investment.”

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The company seeks to help B2B businesses turn ads into sales multipliers by:

• Running person-based ads in sync with sales;
• Gaining transparency between sales and marketing; and
• Tracking revenue impact from the first touch to a closed deal.

The Lowdown

Influ2 V2 represents an advanced stage in the evolution of the company’s unique technology, designed specifically to align the B2B marketing and sales teams around crucial metrics, such as pipeline generation and revenue, and precisely attribute the marketing influence. With this release, Influ2 intends to establish itself as a comprehensive solution for end-to-end revenue marketing.

Back-Of-The-Box Details

Influ2 V2’s revenue reporting capabilities work to bridge the gap between GTM leadership needs and demonstrate the impact of marketing activities on revenue generation. By consistently tracking the impact from first touch through to a closed deal, marketers can continually optimize their campaigns to improve the revenue impact of their advertising efforts. This empowers businesses to measure and analyze the alignment between marketing and sales, ensuring that both teams are working in sync toward common revenue-centric goals.

Who It’s For

Recognizing the importance of marketing and sales alignment, Influ2 V2’s privacy-first technology facilitates and accelerates ongoing collaboration between departments to drive increased conversions by turning ads into a sales multiplier. Marketers can prioritize prospects for sales based on the individual’s engagement with the advertising campaign and provide guidance on the specific advertising messages that resonate with each target buying group and key decision makers. This ensures targets are engaged as people with real interests versus as faceless organizations. Both sales and marketing can track contact-level intent through integrations with CRM and other systems.

What It Solves

With Influ2 V2 multi-stage journeys, marketers can customize outreach strategies based on individual engagement to move prospects through the buying journey. Marketers can create rules based on metrics like number of impressions, clicks, sales outreach and more that customize the prospects’ experiences. This personalized approach ensures that each customer receives the right messaging at the right time, maximizing engagement and conversion rates.

What Makes It Special

Influ2 V2 includes several core features: Cohort designer, multi-stage buying journeys, a sales priorities dashboard with contact-level intent and revenue reporting, which connects marketing influence to sales results.

Contact

Influ2
1250 Borregas Avenue #44
Sunnyvale, CA 94089, USA
Phone: 1 (408) 675-9057

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Growth is not solely about acquiring new customers — it’s also about expanding relationships and keeping your customers happy for the long haul. A net revenue retention (NRR) strategy can help you do all this while scaling revenue and accelerating growth beyond what new customer acquisitions can do for you. 

What Is Net Revenue Retention?

NRR is a way to view customer growth through expansion and retention. Suppose you started the year with 10 new customers each paying you $1,000, summing up to $10,000 on Jan. 1. By the end of the year, you would assess the value of those same 10 customers. If three customers, amounting to $3,000 in revenue, churned, your gross revenue retention (GRR) would be 70%. However, if the remaining seven customers expanded their contracts by an additional $13,000, your portfolio would amount to $20,000, resulting in a 200% NRR.

Why NRR Matters For Marketers

Marketing to existing customers is closely connected to NRR, as a high NRR indicates that marketing efforts are successfully retaining and expanding revenue from the existing customer base. Effective marketing strategies promote upsell and cross-sell opportunities for the existing customer base. Moreover, marketing to existing customers fosters loyalty and advocacy, encouraging customers to stay with the brand and refer it to others.

The Bowtie Model: A Holistic GTM Approach

NRR has not typically been fully leveraged as a pillar of growth because a typical go-to-market (GTM) funnel is optimized toward new, local customer acquisition. If this is your model, you may be asking questions such as:

●      How many leads are we getting?

●      What is our conversion rate?

●      How many new customers are we signing?

But what if you shifted your model framework to a process what Winning by Design Research & Development describes as a bowtie? The left side is the customer acquisition side, and then the right side is the customer lifecycle side.

A bowtie model illustration, created by Influ2.

The Power Of The Bowtie Model

The Bowtie Model helps visualize the best ways to reach your targets. You don’t need to just scale one piece of the bowtie to grow your revenue, and if you execute better in every piece of the bowtie puzzle, you can grow quite a bit faster without herculean feats of valor on the customer acquisition side.

The Bowtie Model offers marketers a big-picture view of the customer before and after the initial sale. Building a deep understanding of B2B decision-makers empowers marketing teams to efficiently engage with customers, improve the overall customer experience and build trust in the brand. It also encourages marketers to deeply understand customers throughout the business relationship, enabling them to create more informed and compelling campaigns.

5 Steps To Improve Your NRR

1. Shift your revenue paradigm from customer acquisition alone to LTV of a customer.

Activate your marketing efforts across the entire bowtie rather than focusing primarily on new logos. Quantify the effect you will have at every stage of the “bowtie” from acquisition throughout the entire lifecycle of a customer and look for ways to accelerate your impact.

2. Make revenue processes that you can replicate with an eye toward growing the long-term value of your customers

Remember, often companies rely on increases to boost revenue, but sometimes that can be detrimental. It’s possible to oversell customers with a higher ASP when, if you sold them at a lower amount, you might actually get a longer lifetime value out of them because they’ll be successful with the smaller amount. And then they’ll expand. And they’ll grow. And you’ll retain them.

3. Optimize revenue at each phase of the customer journey through great experiences that deliver impact

Create great experiences at each stage and touchpoint of the relationship rather than leaving off at solely optimizing everything around new local acquisition.

4. Align the goals, incentives and KPIs across the commercial team

If account executives get compensated solely on the initial deal size for a new logo, they’re going to try to extract every dollar possible on that initial deal versus what’s good for LTV of the customer. So, it’s critical for everyone on the commercial team to align with the appropriate incentives that match the goals.

5. Organize your teams for growth

Having a Chief Revenue Officer (CRO) with full-funnel revenue oversight is ideal to champion the effort. If there’s no CRO and there are multiple chiefs from various organizations, the CEO can create alignment between the groups, having the same definition of what it means to win and corresponding ways to measure success.

While customer acquisition costs might not decrease soon, marketers can still make a significant impact on revenue by supporting an NRR strategy. By nurturing and expanding existing customer relationships, focusing on their lifetime value, and aligning the entire team’s efforts, marketers can play a crucial role in driving sustained growth and success for their SaaS companies.

Joe McNeill is the CRO of Influ2, a person-based advertising company.

The post Using The Power Of Marketing To Unlock Net Revenue Retention In Your Organization appeared first on Demand Gen Report.

The Lowdown

Contextual Audiences by Seedtag is designed to provide advertisers with a new targeting capability that empowers them to engage with modern consumer interests without relying on personal data. Contextual Audiences aims to effectively address the hurdles of reach, scale and privacy that advertisers commonly encounter with the coming deprecation in third-party tracking cookies.

Back-Of-The-Box Details

Powered by real-time analysis of web content, Seedtag seeks to ensure relevant and up-to-date audiences that evolve based on network insights, enabling advertisers to target audiences based on the content they’re currently consuming rather than their past behavior.

By activating Seedtag Contextual Audiences, brands can target precise interests rather than broad stereotypes, capturing their target audience’s attention and engaging them at the optimal moment to maximize campaign effectiveness.

Who It’s For

The introduction of Contextual Audiences showcases Seedtag’s commitment to providing comprehensive and flexible solutions that align with advertisers’ changing needs. As the advertising landscape continues to evolve, Seedtag intends to deliver cutting-edge AI technology to help brands excel in their campaigns.

What It Solves

In response to advertisers’ rapidly evolving and diverse needs, Seedtag’s new contextual audience groups precisely meet each campaign’s unique requirements while respecting user privacy.

What Makes It Special

Seedtag offers brands many ways to connect with their audience:

• Signature Audiences: These audiences have predefined configurations, offering advertisers distinct options for specific verticals and across markets. Additionally, they allow for a certain level of customization to accommodate specific advertiser preferences.
• Seasonal Audiences: These audiences focus on specific temporal events marked by a specific timeframe.
• Custom Audiences: Some campaigns demand a level of specificity that signature audiences might not fulfill. For such scenarios, Seedtag has harnessed the ability to build a campaign-specific machine-learning model that precisely matches the client’s brief. This model analyzes every URL and provides a score based on the most relevant content to help connect brands with a niche audience.

Contact

Seedtag

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Many of these conversations are — as usual — directed at global B2C brands. But while these brands trade in volume, the more interesting story is B2B brands, which trade in accuracy and precision. Rather than using their data to reach bigger audiences, B2B brands can use data to refine their insights to further improve their highly targeted approach.

But wait, it gets more complicated: While B2C marketers are focused on individuals and households, B2B marketers are focused on individuals as part of accounts and buying groups within those accounts. A study from Forrester found that 94% of B2B marketers sell to groups of three or more, with more than one-third selling to groups of 10 or more. To successfully use identity-based advertising to reach an entire buying group, B2B brands need a slightly different approach than their B2C colleagues.

Getting The Data Right

ID-based targeting, which uses a stable unique identifier based on first-party data for more accurate targeted advertising than third-party cookies, is only as good as the data being used. That means B2B marketers need up-to-date and complete information about an entire buying group, which averages between six and 10 people, according to Gartner.

The first (and most important) step is to build out first-party data that’s organized around these buying groups. While B2C marketers have individual customer profiles, B2B marketers need to also have information about how individuals are connected. In a customer data platform (CDP) or other data management solution, this requires an extra layer of organization. When anyone in the buying group takes an action (completes a search, downloads an article) that information is added to the buying group record, not just the individual record. 

Connecting individuals based on the company they work with, their roles and responsibilities, as well as their activity and interaction with the company, requires detective work. While a B2B marketer builds up their own first-party insights about a buying group, they’ll likely need to augment this with partner data that can build out the complete picture, including important signals like intent. With a core record of a buying group, B2B brands are set up to have a view of all their activity across channels and create highly targeted advertising campaigns.

Getting Used To Identity Matching

With a database full of buying-group information, B2B marketers are in a good position to activate ID-based advertising campaigns. This is where those “data clean rooms” come in. Using first-party data for advertising requires a safe and secure way to share information with advertising partners. If a B2B marketer wants to use their own data set to advertise on a specific website, they need to “match” their data to that website’s audience using encrypted IDs. The clean room is where this happens.

Having data clean room capabilities helps B2B marketers securely activate their own data on a partner website and augment it with data from partners to further build out their profile. While some data sets can be matched up using a common key, such as an email address or cookie, in many cases, it requires an “identity graph,” also sometimes called an “identity spine.” Companies with a robust identity graph have enough insights about an audience to match two disparate data sets accurately to make that match even without those two sets sharing a common match key.

For example, if a B2B marketer collects data from activity on their own website, they’ll be able to record any recent site visits, downloads and clicks. However, there might be a partner with lots of additional insights, such as a reseller partner that has a high-volume website featuring a lot of different products. A B2B marketer can “match” the data from their partner site to gain additional insights about their target accounts, such as potential searches for competitor products.

Better Campaigns & Better Results

Of course, all this work to create a great database is just the beginning of a new phase in B2B marketing and advertising. Data becomes the foundation of an omnichannel marketing strategy that is more accurate and more personalized. For example, a marketer could set a frequency cap of an ad across an entire buying group or trigger an email campaign to a specific stakeholder based on the actions of a different stakeholder. In other words, imagine being able to share an article about how secure your products are to the privacy stakeholder right after her boss just downloaded a white paper on your site.

The beauty of identity-based advertising is that it puts marketers in more control while still maintaining user choice and privacy. Not only can they be more precise, but they also get insights back that can build a better picture and inform the next touch in the customer journey. Marketing channels like email have had some of this for years now. Identity-based advertising brings this same capability to the bigger picture. 

Naomi Sherry is the Sr. Digital Demand Strategist at Anteriad, a full-funnel marketing solutions provider.

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