Propelled by the rapid rise of artificial intelligence (AI), mass adoption by global communities (5.3 billion people are now online around the world) and consumers’ seeming insatiable demand for digital products and services, the internet and its vast web of interconnected ecosystems is changing before our eyes.

Understandably, businesses are trying to transform alongside it. Many are struggling to keep up.

With the digital landscape changing daily, staying ahead of the latest trends and consumer sentiment demands more than adapting to change. It requires brands and global enterprises to actively drive it.

The Role Of Experimentation In Digital Marketing

Experimentation-as-a-service (EaaS) provides a framework for actively driving trends.

EaaS, a systematic approach to assessing the efficacy of marketing tools and techniques, isn’t a new concept. It is newly relevant, as AI and machine learning (ML) algorithms are making it more efficient, effective and impactful.

{loadposition GIAA}Most importantly, it allows brands to proactively shape their marketing strategies rather than perpetually reacting to market dynamics.

For maximum effectiveness, brands should test several aspects of their marketing campaigns, including content, design, user experience and channel strategies. In doing so, brands begin to understand consumer behaviors and preferences, elevating sustainability and business growth potential.

For instance, a social media campaign that is continuously monitored and tweaked based on user engagement metrics can achieve significantly higher reach and impact compared to a static campaign.

With EaaS, digital marketers and the brands they support can leverage often-enormous data sets to make their companies more customer-centric than ever before.

AI Data Analytics For Better Decision-Making

Data is an abundant resource for many brands and leveraging it to make informed decisions is often easier said than done.

For instance, global data volume is quickly approaching 175 zettabytes, an unfathomably large number that is the functional equivalent of creating a stack of Blu-ray discs that can reach the moon 23 times.

This deluge of digital information has made data-driven decision-making more of a talking point and less of an operational reality.

Today, less than a quarter of executives say they’ve successfully created data-driven organizations. Despite having more data than ever before, companies are less effective at using this information than they were four years ago.

AI and ML are helping to solve this problem. These technologies are excellent at data analysis, identifying patterns and producing actionable outcomes that would otherwise be unavailable to brands.

As the “Harvard Business Review” succinctly explains, “This means that as a firm gathers more customer data, it can feed that data into machine learning algorithms to improve its product or service, thereby attracting more customers, generating even more customer data.”

While products and services with weak data footprints will inherently provide less data, practically every brand can leverage this technology to create more insights that drive better decision-making processes.

The goal is to maximize personalization. Adobe reported that 71% of consumers say they expect companies to deliver personalized interactions, and with more than three-quarters getting frustrated with brands when they fail to deliver, this is a critical dynamic for effective digital marketing experimentation.

With the average person encountering more than 1,700 online advertisements every month, these personalized encounters are critical to cutting through the noise and maximize marketing ROI.

Make Marketing Experimentation A Priority In 2024

Learning to create a dynamic feedback loop between brands and consumers won’t happen overnight. However, making it a strategic priority in 2024 can significantly impact marketing strategy and ROI, enabling businesses to make informed, real-time decisions that fuel sustainable growth and market impact.

Put differently, using AI and machine learning to distill actionable insights from vast data sets enables brands to forge a dynamic feedback loop with their customers, leading to more effective decision-making and a robust competitive edge.

That’s the power of making change, not just responding to it.

Mario Peshev is the CEO of DevriX, a global WordPress agency providing scalable, long-term technical partnerships along with marketing and business consulting. He is also a Core contributor to the WordPress project, an Inbound Certified marketer and a multi-disciplined business owner with a wide scope of skills.

The post Agile Isn’t Enough For Sustainable Business Growth: How Brands Can Use Marketing Experimentation To Spur Continual Innovation appeared first on Demand Gen Report.

Redactable’s AI-driven platform leverages natural language processing and machine learning to automatically detect sensitive information in documents and redact it. The company plans to use the funding to advance its market reach, visibility and operations.

“With so much confidential information being shared electronically, the risk of data vulnerability for both individuals and organizations is increasing exponentially,” said Amanda Levay, Redactable Founder and CEO, in a statement. “Too much time is spent using black markers or drawing boxes over sensitive data, which is not only inefficient but also ineffective.”

The post Redactable Raises $5.5M In Seed Funding appeared first on Demand Gen Report.

The Lowdown

SOCi Genius offers AI-driven personalized engagements and a sophisticated multi-location review management system. It is designed to ensure a consistent brand voice, protect reputation and optimize ROI through customization, automation and on-brand training models. Using SOCi Genius, brands can boost efficiency while saving costs. 

Back-Of-The-Box Details

Multi-location marketers typically spend hours crafting review responses and making sure their voice is appropriate and consistent across locations. SOCi Genius Reviews takes this off their plates by performing the highly impactful but time-consuming task of writing review responses on their behalf to radically improve productivity.

Genius Social Engagements uses AI to create customized engagements that resonate with brand audiences, allowing them to focus on strategic tasks and drive more meaningful interactions. These tools combine AI with human touch, perfectly blending automation with human oversight.

Who It’s For

SOCi Genius is for multi-location enterprises operating in multiple geographical areas, often spread across cities, states or even countries. These businesses face unique challenges in ensuring consistent branding and customer experiences across all their locations.

What It Solves

SOCi Genius helps boost a business’s ROI by performing time-consuming tasks on the marketer’s behalf. SOCi Genius seeks to always be personalized and on-brand.

What Makes It Special

SOCi Genius provides more streamlined workflows for teams that has been a critical but missing element for multi-location brands. It allows brands to respond to customer engagements at scale and reclaim valuable time throughout their workdays.

Contact

SOCi

Get a demo.

The post SOCi Genius Aims To Streamline Brand Engagements Across Company Locations appeared first on Demand Gen Report.

Signal AI Studio helps businesses train custom AI models to detect meaningful insights from every customer conversation. Specifically, revenue teams can: 

• Automatically capture insights from phone conversations at scale to better understand caller intent and product or service interest, conversation outcome, topics discussed and the performance of the agent on the call;
• Create custom AI models by typing the insight they want to detect — such as if an agent gave a proper greeting — to show specific moments from relevant calls to review and quickly create an algorithm to classify similar calls in the future; and
• Automate follow-up actions using integrations with Google, Facebook, Adobe and Salesforce.

Invoca also announced several updates to its Signal AI suite to help enterprise brands use AI to turn conversations into insights. Those enhancements include:

• Autocapture, which uses AI-powered named entity recognition to extract meaningful first-party data from conversations to enrich customer profiles;
• A new AI and LLM-trained transcription engine that turns calls into text; and
• Caller and agent sentiment tracking that uses neural network models to categorize caller and agent sentiment separately, including how it changes throughout the call.

“Businesses are getting inundated with claims of AI’s vast promise, but few solutions have made a meaningful difference in helping companies grow revenue,” said Nathan Ziv, SVP of Product at Invoca, in a statement. “With Signal AI, you don’t need to be a data scientist to unlock the power of AI. Now, any user can drive revenue by unlocking breakthrough insights from the buying journey, especially the ‘moment of truth’ where consumers make critical purchase decisions. AI models custom-trained for your business deliver the most accurate insights, and now with Signal AI Studio, marketing and contact center teams can create them faster than ever.”

The post Invoca Launches Conversation Intelligence AI Innovations appeared first on Demand Gen Report.

The Lowdown

Market Map is a new AI-based software that is designed to enable B2B sales teams to intelligently refine their ideal customer profile (ICP) and take a data-backed approach to selecting target accounts. More specifically, it automates market research, identifies unique industry segments and quantifies prospects’ similarity to existing customers so sales teams can target the right accounts at the right time.

Back-Of-The-Box Details

Market Map offers a new approach to account prioritization by using the power of generative AI and proprietary machine learning algorithms to improve account scoring and enhance industry classification. Unlike existing data enrichment tools that rely on predetermined industry categories, Market Map analyzes how all the accounts in an organization’s CRM describe their unique products, services and markets publicly, scores each company across thousands of dimensions and then quantifies and clusters accounts based on their similarities. This analysis delivers new levels of actionable industry segmentation.

The software then scores and ranks each prospect account based on how similar it is to the existing customers a company defines as most valuable for more precise account targeting. The result is a visualization of market clusters and a similarity graph that shows which prospects are nearly identical to a company’s best customers.

Who It’s For

Market Map is built for B2B sales teams at mid-sized to enterprise companies who need to quickly identify high-potential prospects in their own CRM that are similar to their best existing customers.

What It Solves

Market Map aims to solve the challenge of selecting and distributing the right accounts to sales reps. Sales teams have the AI-powered intelligence needed to accurately refine their ICP and quickly prioritize the highest potential accounts. Market Map is designed to deliver a hyper-relevant view of prospects, along with a quantified score of how similar each prospect is to an organization’s best customers. This not only instills rep confidence knowing they’re pursuing accounts that have quantified similarity to existing customers, but it also drives efficiency as teams no longer have to waste quota capacity focusing on the wrong accounts.

What Makes It Special

According to the company, Market Map is the industry’s first application of large language models to identify an ideal customer definition through unique industry segmentation. The software is designed to form a contextual understanding of a target market, identify natural market segments and reveal the prospect accounts that most closely match an end-user’s most successful customers.

This level of insight gives sales and marketing teams unprecedented visibility into which accounts to prioritize. Using Market Map, sales teams have the intelligence needed to get a realistic view of their ICP and tailor go-to-market efforts to nuanced groups of similar accounts where they’ve had demonstrated success.

Contact

Gradient Works

Request a demo.

The post Gradient Works Launches AI-Based Account Prioritization Software For Sales Teams appeared first on Demand Gen Report.

It’s definitely going to be hard to top but I think I nailed it!

I feed off the pressure to bring the B2B community a valuable agenda full of sessions that directly speak to their needs with every #B2BMX event, and it’s going to be an exciting summer recruiting speakers and planning what I anticipate will be the best #B2BSMX to date.

The day I came back from Scottsdale and sat at my desk in my home office, planning began. And now as we enter the month of July, I can finally share so muhc information with you! By no means is everything ready to go; we still have much more to put into place before we arrive at the Boston Harbor Encore resort.

Given the crazy circumstances (layoffs, budget cuts, etc.) in our industry and beyond, not to mention the whiplash-inducing shifts in buying behavior, our theme for #B2BSMX this year is “Revenue Rx,” and it’ll be all about the new revenue formula. We’re going to tackle how marketers are embracing AI, intent and machine learning to bring more relevance and value to the new buyer’s journey by applying these remedies to accelerate stalled opportunities.

As always, there will be three full days of content that includes Workshops, sponsor Case Studies, Labs and Lunch & Learns, keynotes and four breakout tracks: Demand Gen Summit, RevOps, ABM In Action and GTM Strategy.

• Networking? Lots of it.
• Food and cocktails? Flowing.
• Valuable thought leadership from the best in the biz? Obviously!
• Perhaps a little gambling in your spare time? That’s up to you!

I’m also excited to announce that we have two INCREDIBLE keynote speakers already on the roster and so many more speakers brewing. My marketing team might hate me for spilling the beans this early, but Roderick Jefferson, sales enablement practitioner and author of “Sales Enablement 3.0: The Blueprint to Sales Enablement Excellence,” will be taking the stage to showcase how B2B teams can turn strategy into action with enablement.

Plus, the one and only Sangram Vajre (former Co-founder of Terminus and current Co-founder and CEO of GTM Partners) is planning his #B2BSMX Campfire session as we speak. We received such great feedback from Michael Ruby’s Campfire at #B2BMX in Scottsdale a few weeks ago that we had to bring it to Boston. And I have full confidence that Sangram will deliver an exceptional keynote/workshop hybrid for our audience (and then some). 

I can’t wait to see them both! And if the feeling is mutual, you’re in luck because registration is officially open. Additionally, if you bring three or more of your coworkers, you can snag 40% off with our group discount. I look forward to seeing you in Boston this summer!

P.S. If you’re interested in speaking at #B2BSMX, submit your presentation here and I’ll be in touch!

The post Get Ready For An Action-Packed Week At #B2BSMX This Summer appeared first on Demand Gen Report.

is designed to leverage AI and machine learning to unlock the reality of customer interactions to help people and companies reach their full potential. Gong’s Reality Platform autonomously empowers customer-facing teams to take advantage of their most valuable assets — customer interactions, which the Gong platform captures, analyzes and then delivers insights in real-time and at scale, enabling revenue and go-to-market (GTM) teams to determine the best actions for repeatable winning outcomes.

The Lowdown

Economic Pulse, a new functionality within Gong’s reality platform, uses AI to give sales, marketing and product teams visibility into customer conversations about economic uncertainty or concerns, surfacing these references in customer interactions. This visibility allows revenue leaders to adjust strategic planning and client communication according to relative concerns, stabilizing the ongoing and potential opportunities pipeline.

Gong Forecast is designed to apply proprietary AI and machine learning technology to surface risky deals, see upcoming forecasts autonomously and understand the “why” behind any changes.

Smart Trackers aim to provide a deep understanding of customer conversations, allowing revenue teams to continuously adapt strategies toward customer needs.

Back-Of-The-Box Details

Economic Pulse works within the Reality Platform to detect common terms and references related to economic uncertainty, alerting sales and revenue teams at the detection of a conversation trigger and how it impacts the current opportunity/deal. In addition to direct alerts, it enables the sharing of customer voice across the organization, leading to cross-functional alignment between sales, marketing and product teams.

With Gong Forecast, companies can monitor every customer interaction to determine what conversation or individual contributed to changes and adjust internal strategies accordingly. The AI-integrated software leverages more than 100 customer integrations, including Google Workspace, HubSpot, LinkedIn Sales Navigator, Salesforce and Slack, to observe and report on customer data related to interactive trends, document completion and more. Customer interactions that impact the revenue pipeline are also flagged directly to the product’s user, allowing for knowledge-based decisions to be made in real-time.

Smart Trackers use AI and machine learning to go beyond keyword recognition and understand the context of all customer interactions captured and analyzed in Gong’s platform. The AI-integrated software allows customer-facing teams to tailor their business, market and priorities relevant to each customer. Smart Trackers are designed to detect the context words associated with dependent variables such as discounts, budget constraints and compatibility concerns.

Who It’s For

It’s pivotal that GTM teams clearly understand the impact of the state of the economy on their customers. When leveraging Economic Pulse, revenue leaders can track, predict and respond to customer concerns — thus leading to informed decisions and sustained organizational growth.

Revenue leaders will benefit the most when implementing Gong Forecast. The program brings to light present-day customer voice to ensure sales planning aligns with customer reality.

Smart Trackers are designed to give revenue teams insight into customer thoughts and concerns that would otherwise go undetected. When implementing Smart Trackers, sales, marketing and product teams can stay one step ahead of execution barriers, drive sales revenue and increase customer satisfaction.

What It Solves

Economic Pulse combats revenue teams’ ongoing obstacle of scaling a business based on outdated and misconstrued customer attitudes toward the economy. The AI-powered platform is designed to ensure real-time and continuous visibility into the customer’s interactions that drive buying decisions.

The lack of information accessibility across revenue teams often hinders efficient sales forecasting. Gong Forecast is designed to store relative customer insights into one source to which all teams have access, ensuring organizational clarity when executing strategic business decisions.

Smart Trackers allow sales leaders to filter through conversations based on a specific question rather than the time-consuming task of sifting through keyword searches in hopes of finding a relevant answer.

What Makes It Special

Leveraging AI and machine learning, Economic Pulse is designed to deliver real-time customer insights that drive business decisions during economic uncertainty. Every interaction is captured and analyzed in real-time, producing insights that support alignment across revenue teams.

Gong Forecast is said to be the first forecasting product to analyze the actual substance of customer interactions in addition to the frequency. The reality-based solution is designed to arm its users with revenue predictability to drive productivity and streamline operational management.

Smart Trackers are designed to find concepts quickly and accurately. It is a user-trainable system that goes beyond keyword recognition to understand the context of customer conversations.

Contact

Gong
201 Spear St. 13th Floor,
San Francisco, CA 94105
Book a demo

The post Gong Launches New AI & Machine Learning Functionalities Within Reality Platform appeared first on Demand Gen Report.

OK, I’m sorry for getting that song stuck in your head, but it’s true: Due to the market expansion powered by today’s interconnected, digital world, it’s easier than ever — in theory — for companies to expand their global reach and engage with prospects in different regions. However, there’s one major hurdle: Language barriers.

While the easy answer might seem to be tossing a white paper into Google Translate, Kathleen Pierce, Principal Analyst, Content Strategy and Operations at Forrester, explained that simply translating content into another language isn’t enough.

“Localization is the act of making something appropriate for a locale, which includes translation plus many other cultural and data elements,” Pierce explained. “You can do translation without localization, and while there’s a time and place for that, it’s riskier. Raw translation can be extremely off base or nonsensical. There are plenty of humorous screenshots of free translation engines botching some translation because it only translated the words, not the meaning. In regulated markets, if you just run your content through some tool that doesn’t know your information, it could lead to significant fines, failed audits, or inability to sell in a region.”

Additionally, localizing assets helps promote customer retention/growth and increase an organization’s competitive advantage as new vendors vie for their market share.

“Startups are extremely nimble these days, and they don’t have tech, design, or content debt,” said Pierce. “Many startups are global from the get-go; they’re going to market in 20 languages with their first launch. And companies who normally didn’t have vendor competition in certain countries are seeing the startups eat their lunch, so to speak. They’re realizing that if they don’t offer a better, more localized customer experience, they’re going to lose market share.”

To remain competitive, the three steps organizations need to take to localize content are:

1. Conducting Research To Understand Regional/Cultural Etiquette  

As for determining where to invest, it’s all about the research. Pierce advised marketers to conduct stakeholder surveys of their customer-facing employees and channel partners to find out how current localization policies affect customers, sales, and marketing.

“I often find that the customer-facing employees are a secret to success, because you can ask them anything and they’ll provide an unvarnished version of the truth,” said Pierce. “Customers can only tell you what’s important to them personally, whereas customer-facing employees have first-hand insights across a wide range of customer scenarios.”

Additionally, Pierce recommended that practitioners tap into their customer and competitive research to see what the “standard of care” is in their industry.

2. Proactively Accounting For Localization When Creating Content

With 42% of practitioners indicating they want content that’s personalized and tailored to their needs, it’s imperative that marketers uplevel localization processes. Pierce advised marketers to incorporate localization at the design stage and treat it as an enterprise function using a hub-and-spoke model with a skilled localization leader at the center.

“You want to put processes and tools in place that enable you to localize content without rewriting or redesigning,” said Pierce. “Skillful planning can eliminate half the time, half the cost, and half the people. There will always be many different groups involved in localization, and you need a skilled localization leader or team at the center to provide vision and management and get the right technologies in place.”

3. Implementing The Right Technologies

According to Pierce, many B2B marketers are using “horribly old-fashioned” manual processes for localization, which is a complex, high-volume, highly technical initiative. “It would be like having your sales reps track their opportunities using spreadsheets and email,” she explained. She continued that the root cause of this is decentralization and lack of leadership, as it’s common for organizations to have many people across multiple departments, such as legal, HR, product, regional marketing, and more, localizing only their content.

“If all these departments are partnering with different freelancers or agencies and treating localization as an afterthought, it’s tough to optimize at an enterprise level,” said Pierce. “Decentralized efforts lead to high costs, slow turnaround, and substandard quality that discourages proper investment by making it appear as a failed area.”

She recommended that organizations future-proof themselves by adopting translation management software, investigating speech-to-speech and speech-to-text localization technologies and training machine translation (MT) libraries for their organization.

To that end, several B2B companies — including Qualified and Contentstack — released GPT-powered AI solutions that assist with translation and localization. Qualified’s offering provides AI-powered recommended conversation responses and on-the-fly translation between languages, while Contentstack’s innovations seek to help content teams create, test and translate short- or long-form content in seconds.

The post How To Prevent B2B Content From Getting Lost In Translation appeared first on Demand Gen Report.

Loops seeks to enable product and growth teams to improve their key performance indicators (KPIs) by automatically identifying concrete opportunities from their data. Key features of the no-code solution include:

• Plugging into data sources and automatically running thousands of proprietary analyses and machine learning models to reveal valuable insights for product and growth teams;
• Identifying and prioritizing the most impactful opportunities and pushing recommended actions to teams; and
• Measuring the impact of actions and refining recommendations over time.

“Most of the AI models in the industry are based on correlation, not causation,” said Tom Laufer, Co-founder and CEO of Loops. “As companies try to make data-driven decisions, they’re actually relying on potentially misleading insights. By contrast, our models are based on causal inference methodology, enabling product teams to understand what leads to a certain increase or drop in a company’s KPIs. It’s a totally different approach that doesn’t waste resources on strategies and tactics that don’t work.”

The post Loops.ai Generates $14M In Seed Funding appeared first on Demand Gen Report.

The Instachat Builder is powered by machine learning and natural language processing to automatically extract relevant content from PDFs, HTML files, document files and more. After extraction, the derived information is translated into question-and-answer pairs that users can review and use to train AI chatbots. Specific benefits include:

• Allowing users to launch intelligent chat on day one of adoption with “98% accuracy,” according to Botco.ai;
• Enabling users to expand the range of topics intelligent chat can competently handle;
• Receiving conversational reporting data directly following deployment and gleaning insights on the user journey, customer retention, SEO and more; and
• Reducing the need for human intervention.

“Historically, launching a chat application was time-consuming,” said Jacob Molina, Product Manager at Botco.ai, in a statement. “Companies needed to manually formulate the question-and-answer pairs they wanted their AI chat to handle. Instachat Builder shortcuts this entire process by automatically transforming any relevant text into training material, allowing our customers to launch powerful chatbots capable of instantly answering hundreds or thousands of questions — with only a few clicks.”

The post Botco.ai Launches Instachat Builder To Enable Rapid AI Chat Deployment appeared first on Demand Gen Report.