Be it software solutions, artificial intelligence, or go-to-market (GTM) strategies — the common thread behind the value is quality data. In GTM, data helps businesses find the right people and companies to sell to and make sure they’re reaching them in the right way. The right data underpins everything from building target account and contact lists to fueling sales prospecting and cleaning existing databases. And with buying centers more fragmented and buyer journeys more complex than ever, B2B data must go beyond mere lists of contacts and companies to include things like buying intent and existing tech stacks. 

This is why I was pleased to see Demandbase’s inclusion in Forrester’s recent landscape report on B2B marketing and sales data providers. At a time when data quality and privacy compliance are top of mind for B2B leaders, and generative AI is transforming the way companies use data, the report offers practical guidance on the changing dynamics in the B2B data provider space and how to evaluate potential partners.

Key Capabilities to Look for

Forrester defines B2B marketing and sales data providers as: Solutions that offer comprehensive data, insights, and data management services to optimize marketing and sales efficiency and effectiveness.

Every business has unique goals and challenges, and the report suggests you begin by understanding the key capabilities required for your highest priority scenarios.

There are two categories of capabilities to evaluate. First, the accuracy and completeness of the data across all key data types, and second, the core capabilities of the provider. 

The core B2B data types include:

• Account Identification: Match unidentified signals to accounts and interpret patterns of engagement
• Company data: Pinpoint the companies that matter most with information like industry, size, location, and news.
• Contact data: Connect with decision-makers using data such as name, title, email, and phone, plus social profiles and connections.
• Technographic data: Know what technologies a company already uses and what they’ll buy next, so you can identify accounts that are the perfect fit for your business.
• Intent data: Determine which accounts are in-market for the products you sell.

But how do you assess whether a provider can deliver accurate and complete data at scale? Don’t take the provider’s word for it. Don’t just think about the volume of their data — think about the quality as well. In order to select a vendor of choice, you need to get hands-on with sample data sets. Conduct apples-to-apples comparisons with the accounts and buying groups you know best. And ask questions about compliance and privacy practices, especially around contacts.

Forrester recommends evaluating other capabilities as well, including real-time search and import of data, matching capabilities, and native / API integrations. The key is to match the capabilities you need to the use cases you have. 

For example, if sales prospecting is critical, prioritize providers with seamless CRM integration and tools that put AI-driven insights directly into seller workflows. If you’re focused on ICP profiling or territory planning, look for robust firmographic and technographic data you can slice to uncover market potential. And if data unification and quality are top of mind, you’ll focus on API-level integration with CDPs, data lakes, and data warehouses as well as data hygiene capabilities and value-added services.

View Your Data Provider as an Ongoing Partner 

B2B data partnerships can’t be one-and-done purchases. The technology and depth of data you need will change over time. Expect to collaborate closely with providers on privacy standards, product innovation and more value from your data. At Demandbase, we make large investments in these collaborations because they directly strengthen our customer relationships and ability to drive growth. We also don’t try to trick our customers into automatically renewing with complex agreements and overly-aggressive opt-out periods.

In today’s landscape, data providers must be strategic advisors that actively guide customers into the future. Forrester’s report emphasizes the increasing importance of this consultative approach.

Key Takeaways for Selecting Your Next Data Partner

As you dive into vendor evaluations, keep these recommendations from Forrester’s report in mind:

• Thoroughly vet potential new primary providers, as switching later causes major disruptions.
• Conduct extensive side-by-side comparisons using sample data sets.
• Align capabilities to your core business scenarios and requirements.
• Ask detailed questions about privacy practices and opt-in data collection.
• Expect significant integration and training investments when changing providers.
• Seek long-term, consultative partnerships that enhance data value over time.

With the right data partner, your marketing and sales teams will be equipped to identify your total addressable market, refine target account selection, engage elusive prospects, and exceed revenue goals. The data landscape is more complex than ever, but by approaching partnerships strategically, you can thrive in today’s B2B marketplace.

To gain access to the full “The Marketing And Sales Data Providers For B2B Landscape, Q4 2023” report (available to Forrester subscribers or for purchase), visit here. 

The post The Marketing And Sales Data Providers B2B Landscape, Q4 2023: How to Select the Right Provider for Your Needs appeared first on Demandbase.

• What is intent?
• Intents role in monitoring and uncovering trends 
• Intents role in proactively enabling your Sales, Marketing and Support teams 

How technology can help banks 

The month of March was pretty dynamic in the world of Financial Services. As someone who works for a company with a vast amount of intent I was curious to look at the trends that superseded March from a Financial Services perspective. I had a hypothesis that the intent would showcase human behavior spiking, searching and reacting around the event. What was the intent showing us? How could other companies use intent and data intelligence to help shape past and present events? Before we get started let’s lay the foundation of intent…

What is intent?

B2B intent data is information collected about the online behavior of companies who are in the market for a specific product or service. B2B intent data should provide insights into the behavior of potential buyers, allowing companies to tailor their marketing and sales efforts accordingly. By analyzing this data, businesses can gain a competitive advantage by being proactive, identify patterns, and trends indicating interest in a particular product or service, and target them with personalized marketing messages and allow sellers to have more relevant conversations.

B2B intent data can include information such as:

• Keywords and phrases that potential buyers are searching for
• Web pages they have visited on a company’s website or other relevant sites
• Whitepapers, reports, or other content they have downloaded
• Social media activity, such as posts or comments related to a particular product or service
• Company information, such as size, industry, and location

Using intent data can help financial services organizations to better understand trends, upcoming events, and alert the marketing, sales, and customer teams who may need to take action.

February – Business as Usual

I began by analyzing over 9k financial services domains, 35k + keywords, over the course of February and March to see if we could use intent to prove out my hypothesis: Intent will showcase there was a large market event in March.

B2B intent data can be a valuable tool for financial services companies looking to predict market events in several ways. Here are 4 examples:

Identifying trends: Intent data can provide insights into the search and browsing behaviors of companies and individuals related to specific financial topics or products. With this data at hand you can be more proactive, identifying trends and patterns that may be indicative of future market events.

Predicting demand: Leveraging intent to predict demand for specific financial products or services can be incredibly powerful. By analyzing the search and browsing behaviors of potential customers, financial services companies can identify opportunities to introduce new products or services that meet customer needs and drive demand.

Monitoring competitors: B2B intent data can also be used to monitor the search and browsing behaviors of competitors in the financial services industry. In this case companies can identify potential threats and opportunities in the market and adjust their strategies accordingly.

Anticipating regulatory changes: Monitoring the search and browsing behaviors of companies and individuals related to regulatory issues. By analyzing this data, financial services companies can anticipate changes in regulations and adjust their strategies to comply with new requirements.

 Had they seen a trend 2 weeks prior with an uptick in keyword searches would this have caused folks to dig a little deeper?

During March 

I think what’s most interesting about March is that we captured the activity, saw the trends increase for Financial Services, and then the traffic went back to normal. The pulse is very accurate when it comes to the intent. You notice in the March graph that alternative banks to SVB start to pick up in the searches around the market event. One can also imply folks are turning to research companies like; Reuters, Bloomberg, Factset for further information.

If we look at March’s longest trending keywords no surprise here… We see a lot of folks responding to the market news.

What can we learn about March events and intent?

Intent can be used as a leading or lagging indicator to identify signals and events that impact your stakeholders. Demandbase can help you set up the systems, keywords, and structure to monitor events that are important to your business and could potentially impact your Total addressable market (TAM). These events could range from natural disasters, layoffs, supply chain, bankruptcy of specific companies, or in this case a market event.

For example, If you were about to invest in a costly marketing campaign to Financial Services companies during this time period… How would you pivot to ensure messaging connects with your buyer during these unprecedented times. Maybe it’s a softer message to let these customers and prospects in the industry know you’re here for them. Or a stronger timely message if you offer risk management or business reputation services during a risky event to capture your audience while this is top of mind in the marketplace. Would this intent have helped your sales & marketing teams be more proactive in the wake of a market event?

Intent data can provide insights into human and business behavior after a major market event in several ways. Here are a few examples:

Changes in search and browsing behavior: After a major market event, there may be significant changes in the search and browsing behavior of individuals and companies related to financial topics. For example, an increase in searches related to financial stability, risk management, or investment strategies. By analyzing this data, financial services companies can identify changes in customer behavior and adjust their products and services accordingly.

Shifts in customer preferences: Changes in customer preferences and priorities. Customers may become more risk-averse and prioritize stability over growth. By analyzing search and browsing behavior, financial services companies can identify these shifts in customer preferences and adjust their offerings accordingly.

Changes in regulatory environment: A market event may also lead to changes in the regulatory environment, with increased scrutiny and regulation of financial institutions. Uncovering these signals can help financial services anticipate these changes and adjust their strategies to comply with new requirements.

Overall, intent can provide valuable insights into the search and browsing behaviors of potential customers, competitors, and regulatory agencies; enabling financial services companies to identify trends, predict demand, monitor competitors, and anticipate regulatory changes that may impact the market. 

By leveraging this data, financial services companies can make more informed decisions and stay ahead of market events and focus their time where it matters most on customers.

The post The world is ending in Financial Services (well, not actually but….) appeared first on Demandbase.

Now, it may be true that we’re constantly producing more data. Especially as the volume of touchpoints on the average purchase journey increases, and measurement instruments grow more advanced. However, more data doesn’t necessarily equate to a better understanding of markets or customers.

For that, we’re still reliant on analysis, synthesis and the power of human capital. So the question that must be asked is: how can sales, marketing and customer success teams leverage insight efficiently?

That’s the role of an insight engine. So let’s talk about what that means, and how you can build one today.

Data silos and operational capability

First, some context. 

RevOps itself is a relatively recent construction. And it’s an important deviation from the standard management structures that came before. Designed to break down the barriers between sales, marketing and operational teams –– RevOps is goal oriented, not function led. Its purpose is to drive revenues, regardless of the skills, channels or teams that might be involved.

It’s this cross-pollination of functional silos and goal-orientation that successful insight engines draw from. Rather than allowing data to naturally fall into the purview of the closest operational hands, businesses that invest in building an insight engine take active steps to foster cross-team data sharing capabilities and a culture of informed decision-making.

In practice, this is a pretty easy activity to set up. Building your insight engine simply involves reconfiguring existing assets and infrastructure. And it’s one that pays dividends as it begins to positively affect organizational culture. Here’s what you’ll need to do:

1. Define data requirements and owners. Start by mapping out the needs of each team. What information do sales reps need to be successful? What do marketers need to know? How can insight improve operational progress towards KPIs? Once you’ve built a list of data points, assign departmental responsibility against each in order to provide clear lines of ownership.
2. Create engaging distribution pathways. After mapping requirements, the next step is to move data from the point of collection and analysis to the people who will benefit from it. For this, you’ll need to select appropriate distribution channels. This might include technological channels such as company intranets, CRM systems or knowledge bases. It can also involve regular process-oriented touchpoints such as review meetings, working groups or regularly scheduled workshops.
3. Formalize management structures. The last piece of the puzzle is an effective management structure that includes regular reviews of your engine, captures new data needs and dedicates resources to continuous improvement.

So, what kinds of insight should your engine produce? The answer, of course, is highly dependent on your context. But we can broadly categorize insights as fundamental truths, tactical knowledge and responsive feedback, based on factors such as frequency of revision and lead time. Let’s look at each category in detail.

Fundamental truths

These are core components of organizational knowledge, derived from active research with clients or customers. Fundamental truths tend to change slowly, and should be rigorously analyzed before distribution.

Examples of business assets that can be derived from fundamental truths include: client personas, market segmentations, competitive analyses and price sensitivity reports. Inputs may include surveys, focus groups, interviews with key clients, intelligence reports and other forms of zero-party data. 

Decisions based on fundamental truths can include pricing strategy, product or service offerings, marketing campaign direction and key sales channels. These are generally large and impactful choices that should be carefully analyzed due to their far-reaching effects.

Lean, tactical knowledge

Tactical knowledge is about being able to move quickly and capitalize on new findings. It’s no surprise that in a modern, competitive environment –– business leaders are asked to do more with less. And to respond fast to changes in consumer markets. It’s these challenges that having access to lean, tactical knowledge can really help.

Integrated research platforms, like InsightHub from FlexMR or Toluna Start, are an ideal gateway to this knowledge –– enabling marketers, product teams and researchers to run quick turnaround projects that place customer opinion at the center of decisions.

Typical data that might fall into this category includes communications evaluations, brand perception tracking, product feature evaluations, new competitor intelligence, A/B testing, behavior or product usage surveys. In short, any question your RevOps team is actively seeking an answer to.

Responsive feedback

The final category of insight your insight engine should handle is responsive feedback. This is about facilitating a two-way relationship between customers and the business. Data that falls into this category includes CX (customer experience) programmes, unprompted reviews and social listening.

What separates responsive feedback from other inputs into your insight engine is that each input represents a one-to-one interaction with a customer. And, more importantly, an interaction that there is an opportunity to individually respond to.

While there’s RevOps value in aggregate tracking of opportunities and threats in review themes, or touchpoint surveys –– there’s also the direct ability to address where things have gone right or wrong. To thank or apologize to customers. To communicate changes that their feedback has influenced. To build individual relationships.

And the good news is that this layer is easy to create. At a basic level, you’ll simply need to choose the touchpoints at which to measure key metrics (whether that’s satisfaction, effort or recommendation) and use a measurement toolset such as Qualtrics CXM or the Medallia Suite to start acting on data immediately.

Delivering RevOps success with data

So, how does this all fit together? If you have a centralized insight team –– your RevOps function may ask for annual strategy setting inputs based on fundamental truths, pass on weekly requests for data that build need-to-know tactical knowledge and put in place pathways for real-time notification of CX anomalies.

Without a centralized insight function, it’s important to both define data gathering responsibilities based on the most appropriate ownership and map out a similar cadence of data. Whichever route you travel –– remember that an insight engine fulfills the same objective as RevOps itself. It transcends departmental silos, is a goal-oriented function, and improves over time through a constant test-and-learn feedback loop.

The post Building an Insight Engine for RevOps appeared first on Demandbase.

However, there are some key factors that can stand in the way of even the most intelligent strategy and prevent teams from achieving success. Some of these potential issues can be caused by malicious users, bots, and fake users online. This group of threats is frequently referred to collectively as the ‘Fake Web.’ While the Fake Web is vast and can impact many areas of business – for the purpose of this article we will focus on the ways in which ABM departments and leaders can face the consequences of bad actors online.

Inaccurate Targeting

When it comes to attracting net new customers through ABM, one of the key tactics used is paid advertising. In order for campaigns to be effective in achieving ABM goals, they must be highly targeted and their messaging must resonate with the end viewer of the ad. Because of how specific these advertisements are, showing the wrong ad to the wrong audience can result in confusion and ultimately loss of customer trust. For this reason, a lot of time and data is put into the creation of audience lists for these campaigns. These audiences can be built on certain personas, target account lists, intent keywords, demographics, and other key factors.

The marketer then trusts that these campaigns will show the right ad to the right person at the right time. However, what if those campaigns somehow became polluted with bots and fake users? Unfortunately, this is not just a theoretical problem, but a harsh reality that many marketers are not even aware of. When fake users show high levels of engagement with previous campaigns, future campaigns then become optimized toward additional bots. This leads to wasted ad spend that could have been better used on real potential customers.

Skewed Conversion Metrics

When bots and fake users infiltrate ABM tactics, they don’t simply stop after clicking on an advertisement. In many cases these bad actors make their way to the brand’s website – either through those ABM ads, or organically – and continue to wreak havoc on the business’s key objectives.

One of such ways this occurs is through form fills and lead generation fraud. Bots may seek to fill out a form in order to gain access to privileged information or to access additional data about a company or their products for malicious use. But regardless of the motivation, these fake users do not have the intention or ability to convert into real paying customers and thus, skew important success metrics like impressions, engagement, site visits and more. Furthermore, it can confuse marketers when it comes to which channels they should continue investing in, which conversion points are the most compelling, and what level of interest their audience actually has in their offerings. In this sense, fake traffic can poison everything.

Sales and Marketing Misalignment

The next disruption we’ll discuss is a tale as old as time – marketing and sales misalignment.  There are many things that can cause friction between marketing and sales teams, but one of the most prevalent is this: marketing works hard to send leads to sales, but then sales is dissatisfied with the quality of those leads and thus loses trust in marketing. This cycle continues as marketing also gets frustrated because they are putting a lot of effort into acquiring those leads and may feel unappreciated.

When bots enter the picture, this problem only continues to grow. When bots are filling out forms and requesting demos, not only are they skewing metrics as previously mentioned, but they are also entering into funnels and taking up additional resources. This can include re-marketing campaigns, email nurture flows, and – last but not least – valuable time from sales that could be better spent on real potential customers. If this continues, it will add to the distrust of marketing leads and sales team members might choose to shift their focus toward leads from other – potentially less valuable – lead sources.

Reputational Damage

Since ABM strategies and tactics are designed to be highly targeted, and present very particular use cases and examples to the audience that will find them most relevant. If this goes awry, potential customers will become confused and might dismiss your offering as not relevant, when in reality they were simply reached with a message intended for someone else. Additionally, if creative is tested and implemented based on inaccurate information, and then decisions are made about which creatives work best and should be invested in more heavily, it’s extremely important that those tests are done with correct audiences and real potential buyers.

Otherwise, resources will be poured into channels, ads, or messages that might not resonate with a particular buyer, or worse – might not resonate with anyone. As you can imagine, unintentionally testing messages with groups of bots, or measuring success against how bots interact with campaigns can lead to a great deal of confusion, detrimental decision-making, and potentially irreversible reputational damage.

So What are Marketers Supposed to Do?

Each of these key ABM obstacles caused by the Fake Web can seem startling on an individual level, and outright overwhelming when considered collectively. However, there are steps that marketers can take to avoid the issues caused by bots and fake users and make strides to protect their business, increase marketing effectiveness, maintain favorable brand reputation, and ensure analytical accuracy.

Some of these steps are a bit tedious though and can include: sifting through ad campaigns and looking at the quality, frequency and source of interactions; auditing contact databases and CRMs; frequently creating new audiences built from fresh contacts that have proven to have genuine interest; and looking for anomalies within analytics platforms. Fortunately though, there are a few pieces of technology that can make these processes much more seamless and much less time consuming. This can include a Go-to-Market Security provider like CHEQ, and a smart and accurate ABM marketing platform like Demandbase.

The post How the Fake Web Impacts ABM appeared first on Demandbase.