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B2B SaaS Funnel Conversion Benchmarks

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B2B SaaS Funnel Conversion Benchmarks
Blogs

B2B SaaS Funnel Conversion Benchmarks

B2B SaaS Funnel Conversion Benchmarks

Benchmarking your conversion rates underscores any lack in your sales funnel. Can it also help your team max out their conversion potential?

Keep your friends close and enemies closer. The competition in the B2B world is extensive. With the introduction of AI and automation tools, businesses are taking shorter, reliable, and efficient routes to improve their operations.

But marketing and sales are two areas of business that you cannot rush, or take a shortcut for. These processes are highly detailed and require the utmost attention. We are doing this differently, but some traditional methods still exercise precedence.

It’s the same for B2B SaaS funnel conversion benchmarks. These benchmarks do not pit us against our competitors but provide insight into the performance and roadmaps they use in the B2B SaaS funnel.

The race is to seem unique to the customers amidst all the businesses that offer the same services. You can master the game. A healthy understanding of what the competitor is doing differently helps improve business strategy and highlight the pain points to revamp your marketing and sales efforts.

The sales funnel tracks how a customer is guided through a purchasing process.

A funnel is a tube-like object with a wide top (like a cone) and a thin-elongated bottom that guides liquid substances into containers with a narrow opening.

This is technically what a sales funnel also entails.

Now imagine the wide top of a funnel with several potential prospects at the beginning of the funnel. This is where you create awareness for your business and try to poach as many leads as possible.

Sounds simple, right? However, a single step (in theory) comprises several more curated processes and measures.

At the entry point or top of the funnel (TOFU), you create awareness for your business through social media, blog posts, newsletters, and paid ads. Not only does your business require traffic and engagement, but it requires one that is defined and condensed. It is impossible to cater to everyone, so the primary objective is recognizing a niche market.

With the help of outreach, prospects become aware of your business, while the potential buyers understand why they might need you. You have to exude an appeal to attract the targeted audience towards your brand – we can offer solutions to fix your problems.

As these prospects move forward to the middle of the funnel (MOFU), the funnel narrows down. In every stage, qualifying leads are filtered out (Remember that a funnel is a significant tool used for filtration) and taught how your offers can provide them with a solution. The focus remains on qualifying leads where you investigate their intent. You track their course based on whether they are interested in your SaaS solutions or have the resources and authority to make the final sales decisions. A qualified lead may significantly help boost your win rates.

This is what lead nurturing is about.

  1. The leads recognize their problems and become aware. The prospect identifies their problems and the different variables associated with them.
  2. They notice and gain interest in your business. Your offer could provide them with solutions for a problem-less future.
  3. They do their research to make the final decision. After becoming aware of your business and the possible solutions, they begin to learn more about you to find out whether they are the right fit for you and whether you are the right fit for them.

More modern consumers are diligent in their research. They search through, study, and analyze different variables across the internet before taking the next step in the funnel.

So, your lead nurturing process has to be interactive, creative, and engaging to hook the prospects from the beginning to the end of the sales funnel.

Keep them engaged and hold their attention – the most significant part of the funnel where the sales process begins.

Providing more detailed information regarding your offers – pricing structures, guarantees, and proofs (reviews) increases the possibility of conversion. This eliminates additional leads who are not ready to commit i.e., purchase your products or services.

Besides, it should give you a rather concrete idea regarding which prospects are guided until the last stage of the funnel – a close – representing the final stage or bottom of the funnel (BOFU). When the prospect finally leaves the funnel, you have lost or won the sale, turning the qualifying lead into a successful customer/buyer.

This is what the last stage in the funnel entails. Generate sales. Offer compelling but competitive pricing, push your leads to the checkout pages, customize them, and boost conversion rates. But is it as easy as it sounds? No, it’s easier said than done.

In the B2B SaaS landscape, you can adopt benchmarking to evaluate how your product is fairing against your competitors using specific metrics or KPIs.

Sales funnel metrics are the steering wheel of your marketing bus here. These metrics track and highlight your success or areas of improvement, monitor, quantify, and improve the overall sales journey.

Do you want to know if the budget and resources spent on your marketing efforts benefit your business? KPIs will help you here. Funnel metrics can be considered as KPIs that track the efficiency of sales and marketing teams in closing a lead.

Assume that these KPIs are your exam results. Don’t these results show how much effort you put into your preparation and how efficient those tactics were? The same applies to the funnel metrics. They help analyze and outline the efficiency of your marketing tactics.

This is why conversion rate is a significant sales funnel metric. The world of B2B holds the measurement of your marketing or sales effort to the highest potential value. Your conversion rate measures how many prospects move through each stage in the funnel, and lastly, how they convert from potential leads into customers.

Tracking and optimizing SaaS conversion rates throughout the sales funnel can be optimal to drive product growth. The ultimate objective is to improve efficiency, maximize results, and enhance the entire customer experience, from lead nurturing to retention.

If the offers do not resonate with you, the funnel could end on a road with a dead-end for the prospects. This is possible in every part of the sales funnel. While the closer a lead is to the bottom, it increases the likeliness that it could lead to a close (won/loss), but they could defer too. The possibility is never nil.

What does it all narrow down to? You are guiding your business’ website visitors to become paying customers.

The space of B2B SaaS is competitive and complex.

More often than not, nurturing leads does not result in a sale or won. You wish to understand why and also record why your marketing efforts are not reaping any fruits.

What do you measure them against? B2B SaaS benchmarks.

B2B SaaS funnel conversion benchmarks are not the law, but guidelines differ from business to business.

These depend on factors such as the complexity of your sales process and the targeted market size. These allow you to regularly measure the success rate of your efforts and improve your sales process.

Setting specific industry standards – B2B SaaS marketing benchmarks – offers your business an idea regarding how your sales funnel performs compared to others within the same industrial domain. It foregrounds an in-depth insight into the areas in need of improvement. By understanding where you stand, you can set targeted goals that meet your marketing objectives but are realistic and also optimize your sales process.

However, in case of any drawbacks, these benchmarks pinpoint how your sales and marketing teams can relocate the resources and reiterate their approach to generating maximum potential leads. It begins at the top of the funnel, no matter how insignificant that stage might seem. Unsatisfactory strategies or too many funnel stages also result in low conversion rates.

But how do we dictate what ‘good’ or ‘low’ or ‘successful’ conversion rates are?

There are six crucial stages in the B2B SaaS funnel:

  • Website Visitors
  • Lead: A lead is a website visitor who may have shown interest in your offer and submitted their contact information.

If a prospect has signed up for a demo, continues visiting your websites, and has agreed to communicate with an executive, they are a qualified lead. Actions undertaken by the sales and marketing teams vary depending on the services or products offered.

  • MQL: MQL is a Marketing Qualified Lead who is the lead interested in your services but may or may not have purchasing intent.
  • SQL: SQL is a Sales Qualified Lead interested in your services and has purchase intent.
  • Opportunity: An opportunity is a lead on the way to closing the offer and has a contract secured in hand.

In the SaaS landscape, this stage is also known as PQL or Product Qualified Lead, where the prospect has signed up for a trial or demo period of your services and attained value.

  • Closed: This could end in closing the offer however, it is not always a win. The sales team could also end up losing the deal.

The last few stages differ broadly across industries. For the B2B SaaS industry, qualified leads convert to product-qualified leads and then lastly to paying users.

Now, that we have a straightforward understanding of the B2B SaaS funnel stages, we explore B2B SaaS funnel conversion benchmarks.

What Are the B2B SaaS Funnel Conversion Benchmarks?

As mentioned previously, your business must track their conversion rates i.e., to quantify their marketing efforts and if they are harvesting any results (Your CMO wants numbers!). The higher numbers that marketing brings in, the more credible their efforts become for the business.

Overall, the steps or stages in the sales funnel are highly dependent on industry type and size, marketing and sales strategy, trial type, and the engagement model.

We understand how crucial conversion rates and numbers are to establish our profitability, but how do we know these numbers are good?

This is where B2B SaaS benchmarks enter the chat.

These benchmarks make it crucial to tap into the performance and efficiency of the conversion stages in the SaaS funnel. Here, we dive into the significant benchmarks that drive successful conversion rates:

Website visitors to Lead Conversion Rate Benchmark

The metrics measure how many website visitors convert into qualified leads in a specific period. For this stage of the funnel, which is its entry point, the conversion rate benchmark for SaaS industries falls at a rough average of 7%, according to Capterra. This is considered the free trial conversion rate – the percentage of prospects who visit the business website and sign up for a free trial.

This depends on the company size as well as the model. For example, free trial models have a conversion rate of 25% whereas for freemium models, it is approximately between 1 to 10%.

B2B SaaS conversion rates differ along with the channels. The SaaS conversion rate depends on the competitor’s sales channels and engagement model.

Free Trial to PQL Conversion Rate Benchmark

This funnel stage illustrates the percentage of previous users who have interacted and engaged with the free trial services and also draws value from the same. In a more general sense, it also signifies the MQL to SQL conversion rate benchmark.

Diverse businesses use freemium models to collect the lead’s data and enable the sales team to chase them down. The average free trial conversion rate benchmark is 1-10% as mentioned above.

Under freemium, we can find a classification of conversion rate benchmarks – those who used credit cards and those who didn’t.

For a free trial to PQL using credit cards, the conversion rate benchmark is approx. 50%, states Tatango.

Meanwhile, for those who didn’t use credit cards, the conversion rate is nearly 25% based on a survey report published by Softletter. This decrease in conversion rate in this scenario helps provide insight into the user behavior due to friction in payment.

PQL to Paid Customer Conversion Rate Benchmark

While statistics show that not a high percentage of MQLs convert to SQLs, PQLs have showcased a 20-40% conversion rate into paid customers. The benchmark provides insight into the percentage of PQLs the sales team helps convert to paid customers.

Gainsight’s Product-Led Growth Index states that compared to a 9% median conversion rate from free to paid accounts, we can witness a growth in conversion rates for free trials using PQLs – a 2.8x conversion rate.

Marketing efforts of your time nurture and qualify leads, but by identifying PQLs, you gauge the product ROI and negotiate the sales contract. Here, personalized outreach goes a long way.

Benchmarking your performance will outline where our closest competitors beating us and how, says Gartner.

The benchmarks provide an in-depth insight into quantitative data i.e., sales funnel metrics or KPIs. It illustrates simple facts regarding your average conversion rate compared to your competitors and how your buyers and clients measure against them. And most importantly – the fractures in your sales funnel.

By correlating your quantitative data against the benchmark, you can map the future course of your marketing and sales strategies. Additionally, you can modify your landing pages, CTAs, content produced, and lead nurturing techniques to improve the SaaS funnel.

When you adapt strategies that work for your competitors i.e., what they are doing differently along with the channels they are utilizing, you comprehend your weaknesses and pain points.

However, benchmarking your efforts and processes is only half the concern. The B2B SaaS marketing benchmarks will allow you to skillfully strategize how to boost your conversion rates up to industry standards. You begin to work towards securing the whole when you understand the lack.

Are you ready to secure the leaks in your sales funnel and scale up your conversion potential?

White-Label-SaaS
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White Label SaaS for Business Growth

White Label SaaS for Business Growth

B2B marketers are on a quest to expand their customer base and sustain brand value. Find out how white label SaaS can help you streamline this journey.

In the dynamic world of business, white label SaaS platforms are perfect for brands that want to sell software but lack resources. According to a survey by Statista, 75% of web and cloud-based businesses use white label solutions.

They are a good choice for businesses looking to expand their service portfolios without internal development. When you buy software rather than build it from scratch, you can save time, resources, and money while accelerating your business growth. It helps you deliver tailored experiences to your customers. Businesses like yours can leverage white label SaaS services, rebrand, reprice, and sell them under your banner.  

Top 3 benefits

These software solutions present various opportunities that can help boost your brand reputation and accelerate the ROI cycle. White labeled tools make it easier to integrate a software solution without building it from scratch.

  • Speed-to-Market: You can enter the market faster while cutting out on the long duration of building software from scratch.
  • Cost-Effective: Developing software solutions can be an expensive process involving large amounts of resources. This white label SaaS solution offers a cost-effective alternative. The only expense from your end is the licensing fee. 
  • Brand Visibility: You can utilize a product built by experts to enhance your brand presence without the stress of hiring a development team.

Types of products that can be white labeled

Social media management software

White labeling this software helps to seamlessly manage, post, and respond to social media interactions. A white-label social media platform allows you to brand systems that are already functioning rather than building them.

Mobile applications

When white labeled, mobile apps allow multiple brands to use the same function under their brand name. This explains why there could be many apps in the market for a single function like payments linked to business websites, for instance.

SEO and SEM management software

When SEO services are resellable, their popularity can increase multi-fold because you may not have the resources to figure out how to implement SEO effectively. White label services for this application allow you to provide SEO solutions to your client network even when you are crunched with time.

Email marketing software

Email marketing is a keystone tool for any B2B brand. The ability to track email campaigns is the need of the hour. With white label software as a service, you can add your branding to the software, generating customized dashboards. The selling point here is the ability to personalize the solution conveying your brand’s voice.

Marketing Automation Tools

Marketing strategy is like an endless loop, requiring tweaks periodically to cater to your target audience and accomplish the goals. There are many components involved in a marketing plan and if not managed well, the entire system can become imbalanced. That’s where marketing automation tools come in handy. You can automate daily tasks, and view comprehensive analytics. And with white-label products in marketing automation, you don’t have to stress about building them. They can seamlessly streamline your overall marketing efforts.

CRM software 

CRM has become an integral component of businesses with a medium to high customer base. A good CRM software can propel your business to great heights. As per a statistical report, by 2025, revenues from CRM systems are estimated to reach $80 billion! Brands can make the most of this high demand with a white label SaaS CRM Software. White label CRM comprises collaborative models, where software developers and experts develop applications to help other companies navigate the competitive market. This makes the tool available to users to organize contact information and build strong client relationships.

5 Best White Label SaaS Platforms

We have prepared a list of top white label solutions for you to choose from:

ActiveCampaign for marketing automation

image 5

(Source: ActiveCampaign)

With ActiveCampaign’s automation services, you can track your engagement analytics and performance reporting. What’s more— it allows you to derive data from multiple sources, automating your marketing. You can sell this software service under your brand banner or customize its features to match your business goals. Alternatively, you can utilize the white label tools for all enterprise-level accounts and small businesses.

AuthorityLabs for SEO

image 6

(Source: AuthorityLabs)

If you are looking for a white label analytics tool that can provide remarkable SEO-based services, then AuthorityLabs is your choice. This platform greatly simplifies monitoring of the SEO performance of campaigns by integrating relevant keywords with high search volume and organic keywords and automating local and mobile ranks to collect daily reports. AuthorityLabs allows you to track the performance of your SEO campaigns with their white-label services. It offers a highlighting feature for customizing the reports to align with the solutions your prospects seek.

SocialPilot for social media marketing

image 7

(Source: SocialPilot)

SocialPilot helps you to stay on top of everything that happens online. This white label SaaS platform can be your go-to for staying ahead on social networking. You can amplify your customer reach multi-fold through its unique features, such as social media scheduling, publishing, and analytics. What makes it stand out is the flexibility it offers to use these services under your banner.

SalesPype for CRM automation

image 8

(Source: SalesPype)

This platform is a good fit for your business if you want to manage client relationships efficiently. What makes it a viable choice is its white label program for marketing agents, consultants, and enterprise clients who intend to resell their CRM and increase their revenue returns.

Simvoly for building websites and funnels

image 9

(Source: Simvoly)

Simvoly is your best bet if you are seeking a white label SaaS tool for building websites and funnels. You can experience these two benefits together in a single platform. In this way, it helps you rapidly expand your business in no time. 

Wrapping up

White label SaaS platforms are a doorway to expanding your brand presence and getting more recurring revenue. You can purchase solutions that will enhance the performance efficiency of your business while conveying the brand voice. When you opt for this technology, you deliver innovative software services under your brand banner. Whether you are starting up or already have an established brand image, these tools can bring you great benefits if you know which platform is best suited for your business. The list of best white label SaaS tools we have shared here will make it easier for you to select the ideal platform.

The Rise of AI-Driven Subscription Business Models
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The Rise of AI-Driven Subscription Business Models

The Rise of AI-Driven Subscription Business Models

Modern consumers are turning to subscriptions. Can businesses boost the longevity of subscription models to cash in on this trend? 

Convenience over conveyance and access over control is the motto of our world.

Technological developments lie at the core of this postmodern age. Customer expectations have increased. Businesses expand rapidly due to an overwhelmingly large customer base. And, as subscription services multiply, it has become time-consuming to handle a huge volume of customer data while tracking real-time insights.

To catch up with these changes, a system that aligns with and prioritizes customer preferences becomes necessary.

Businesses have begun adopting new tactics to counter them—one of them being AI-driven business models which has led to AI becoming a prototype for business models across different domains.

But this realization is not a modern one, the idea came into existence several centuries ago. It was in the 15th century when ease of access integrated with predictability and stability to craft a more predictive and recurring business model – subscriptions.

In an age where technology was not the norm, publishing houses depended on customer loyalty while the customers relied on content quality.

The basic understanding behind subscriptions as a recurring revenue model for businesses is set in stone. It continues to cater to customer demand and thrive on customer loyalty – a strategy that has remained static ever since.

However, subscription businesses were not introduced in the 20th century.

The history of traditional subscription models reaches as far back as the 15th century when the services ranged from milk deliveries to magazines. On the other side, modern business models rose through the crux of modern computing in the second half of the twentieth century.

In 1994, The New York Times publication, “Attention Shoppers: The Internet is Open”, announced the first-ever Internet retail transaction completed using a credit card. A deterrent in this joyous moment? The privacy concern.

In the article, Commerce.net, a US-based government organization promoting e-commerce transactions, feigned the need for an easy-to-use industry standard for protecting Internet transactions. Have subscription business models become that industry standard?

In the same year, Amazon.com established a marketplace for books and CDs. This everything store opened new avenues for e-commerce transactions, setting the benchmark for modern subscription models.

In this rapidly evolving and complex digital landscape, subscriptions took a giant leap from print. We have landed in the era of SaaS (Software-as-a-Service) where digital services and products are acquired on a recurring basis, welcoming the modern variant of subscriptions.

During the late 2000s, Apple kickstarted the digital subscription models by offering subscriptions to content-based apps such as music, video, magazines, etc. Meanwhile, SaaS businesses such as Salesforce and Microsoft have also significantly contributed to and popularized the growing subscription economy.

Today, countless companies are adopting subscription business models with tailored experiences offered through data analytics and personalization.

Since then, a systematic integration of AI with machine learning has reshaped the model’s capabilities. The primary cause of concern that plagued traditional subscription services – safer transactions and privacy of their payment information – has been addressed by introducing blockchain technology. On the other hand, IoT has also increased connectivity between subscription devices.

Have we strayed too far from the real purpose behind subscription models?

If you closely study how subscription models work, you notice that it is inherently a symbiotic relationship between businesses and their ‘regulars.’ Recurring buyers are the key ingredients for subscription businesses and are crucial in popularizing subscription models across diverse domains.

Owing to its growing popularity, how both – regular and potential buyers – access, interact, and engage with these services has significantly changed. Businesses have introduced personalized subscriptions to appease a diverse demographic.

With more and more users seeking personalized experiences, organizations are introducing customizable subscription packages to chase qualifying prospects. And, they are not mere trends that might fizzle out shortly.

So, subscriptions became the benchmark for optimizing customer relationships and business profitability.

However, the underlying concern is how companies tweak the existing subscription models to gauge more revenue instead of developing new ones.

Have you ever noticed pop-ups announcing you can only proceed further after subscribing to a premium plan?

Limited access. The new maxim of subscription businesses.

With growing consumption habits and unique patterns, we want to control access. For this, we play tug of war with subscription providers. The more we seek the content behind the pile of subscription services, the more they restrict and monetize our access.

To say that subscription businesses have begun utilizing a new marketing gimmick would be an understatement. With different subscription plans, they offer you personalized recommendations using chatbots or pop-ups, making AI – the basis of future business models.

What has brought about these changes? The use of personal data.

The end goal behind AI-driven models is bridging the supply-demand gap. With a surge in services in the market, the demand has escalated and traditional models have proved detrimental to this growth. Customer demand is increasing at an alarming rate. So, subscription businesses come to your rescue with personalized, swift, and reliable solutions.

Coupled with the prowess of AI, businesses rush to execute relevant changes in how customers interact with subscription services. And now, with the help of this cutting-edge technology, companies can effectively curate creative and cost-effective business models increasing customer lifetime value and gaining valuable user insights.

The advent of AI might as well be considered the turning wheels required to revolutionize subscription business models.

By removing the need for multiple liaisons, businesses can improve their customer experience by employing AI tools. This could enable them to remove the middlemen between the providers and potential users – a splinter in the traditional models.

Besides, the broader landscape of consumer behavior itself has taken a drastic turn. AI analytics condenses complex and extensive consumer data to simplify service packages and develop subscription models through consumer pattern recognition.

We have transcended one-off purchases to a subscription economy that relies on access, convenience, and personalization – the cast iron of AI-driven subscription models.

AI-enabled CRMs have proved beneficial in analyzing user history, demographics, and browsing behavior to churn out subscription packages that will resonate with prospects.

With individual preferences taking precedence, the latest business models aim to introduce seamless customer experience and accordingly optimize their services.

How do they bridge the connectivity gaps?

By integrating circular models with their subscription models.

Previously, businesses engaged users through a linear value chain. But that has been reiterated into a circular chain to align with the evolving digital landscape. In the circular economy, the service provider retains the ownership of their product or services, and the user pays for its use over a limited period. At the end of this period, the provider is responsible for upgrading and maintaining these services. This establishes a continuous dialogue that helps the businesses outline the user’s usage patterns – another evolution in business models exploited by subscription businesses.

Moreover, traditional subscription business models have always analyzed propensity scores to anticipate whether users will churn or subscribe to your services. These numbers are important, but unreliable and futile without the necessary software to put them to use.

To boost the relevance of these numbers, newer subscription business models plan to align with the dynamic technological landscape.

This is where AI plays its role.

Subscription business models understand what you want them to do through predictive analytics. It employs AI, machine learning, statistical models, data analysis, and user behavior to predict future outcomes.

Predictive analytics has three significant techniques – regression analytics, neural networks, and decision trees. But decision trees are one of the AI techniques that influence and improve subscription models.

AI-decision trees categorize data according to different variables. This method works effectively to understand a user’s behavior and ultimate decision. By classifying the customer base into specific groups, businesses leverage predictive analysis to predict their pattern alongside tailoring content to reach a wider audience.

As the name conveys, this classification model resembles a tree where the branches signify potential choice, and the leaves represent the result that the decision ultimately leads to. This simplifies the entire process of customer pattern recognition improving the capabilities of the subscription business models.

The newly developed subscription models not only analyze but also shape the customer history, shifting the central focus on ‘direct-to-consumer’ subscriptions and boosting the customer lifetime value (CLTV).

The upgraded subscription business models are AI-empowered, integrating lead generation and customer assistance into a unified experience.

Why are more and more businesses adopting subscription models?

Subscription models are a recurring revenue stream for companies where retention and preservation of customer experience take center stage. How have they done this?

Through recurring upgrades and maintenance of subscription packages, the sharing economy ensures increased service utilization and higher income per unit. The newer subscription models consider a range of pricing strategies. Due to this, introducing usage-based pricing has become paramount in boosting customer retention and conversion rates.

The result? Hybrid subscription models that align their services with unique consumption habits.

If we want an answer to why more businesses are adopting subscription business models, regular revenue stream and customer retention seem the most plausible reasons.

Tien Tzuo, the founder of Zuora, labels future subscription business models as the “total monetization stack.”

A glimpse at the future of subscription business models reveals an effective merger between sales and service models. Formerly, self-service models catered to users who favor their research, whereas account-based models served those who sought tailored options.

Through the help of AI techniques, subscription businesses have leveraged both these models to address the mutual dependency between subscription and consumption.

A step forward from traditional subscription models that barely offer any competitive edge.

Is there space for subscription business models in the future market?

Subscription – a direct manifestation of consumption culture, is also a new middleman between content and consumers.

With intensifying consumption habits, subscriptions require sustainable subscription models that meet the requirements of their businesses and their users.

The question persists: will AI-enabled subscription models develop into a significant tool for businesses to market their services skillfully, or will it become a stumbling block across the evolving habits of the consumer culture?

Utilizing Industry Mapping to Ace the Competition in Your Business Domain
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Utilizing Industry Mapping to Ace the Competition in Your Business Domain

Utilizing Industry Mapping to Ace the Competition in Your Business Domain

Determining the differences between you and your competitors is the key to sustaining the dynamic market. How can industry mapping help you in this arena?

Businesses with a robust customer engagement framework have a chance of retaining 89% of their customers. But, the B2B landscape is highly competitive, where getting customers on board can be challenging, let alone retaining them. Assessing competition from every angle is crucial to developing strategies and adapting your offerings to meet the prospects’ needs. The good news is— you can leverage industry mapping to tip the scales of competition in your favor.

Industry mapping is an assessment tool that provides an overview of what is happening in your domain, such as demand-supply statistics, the extent of competition, prospects of considering technological changes, and external influence.

Analysis of an industrial niche accounts for the various economic, technological, and environmental aspects that shape the competitive landscape. When you delve into these components, you can identify the strengths and weaknesses of your brand. You also become aware of the opportunities and potential threats present in the market.

Industry mapping is a perfect tool for learning about your company’s position relative to your competitors. Let’s dive into more details of this strategic process.

Significance of mapping your specific industry

As you know, the business sector is highly competitive, where achieving a cutting edge is crucial for staying ahead. This is where industry mapping chips in by helping you weigh the market conditions. You view the big picture of the demand and supply chain and the financial returns you can receive from your business. It enables you to estimate brand positioning and derive data to understand whether your business is expanding or reaching saturation point.

A roadmap of this process guides entrepreneurs like you to discover untapped opportunities. To be precise, industry mapping helps you-

  • Overview of your competition: find out who else is in the market, what they are doing, and how you can stand out.
  • Identify opportunities: determine the scope for growth and prevent potential issues by visualizing the trends and patterns.
  • Improve strategy planning: know what is happening in the industry’s landscape and make it easier to compete effectively and expand your business.
  • Remain updated: it informs you about what is happening in your industry so you can adapt to changes and stay ahead of the competition.
  • Make informed decisions: armed with insights, you can adopt better fact-based decision-making, which increases your chances of success.

Key elements of an industry analysis

We have prepared a list of elements that form the core foundation of the industry mapping:

  1. Market size and growth: Assess the current market size and your brand’s growth trajectory.
  2. Key players: Identify major companies and competitors in the industry.
  3. Trends and changes: Analyze current trends and anticipate future shifts in the industry.
  4. Competitive landscape: Evaluate the intensity of competition and strategic approaches used by competitors.
  5. Opportunities and threats: Identify potential growth opportunities and risks that hinder business operations.

Benefits

These advantages offered by industry mapping make it a must-have for your business:

Top 5 Benefits of Industry Mapping

Know your competitors

When you learn more about other businesses in the same domain, you know how to design effective marketing strategies for your offerings to sustain the competition. The intrinsic characteristics of industry mapping pave the way for understanding your competitors on a deeper level. You can conveniently retrieve data, analyze products, and strategize your social media and marketing campaigns.

Evaluate industry trends

Staying tuned to the industry trends is essential for aligning your offerings with the solutions your target audience seeks. With this overview, you can draw inputs about the competitive landscape within each segment. In this way, you can apprehend how your brand can remain ahead of the competition. All this data, when leveraged, will empower your brand image and help you adapt to the evolving market demands.

Analyze consumer behavior patterns

Not knowing your buyer’s preferences and purchase history is like navigating without a map. The buying behavior of your target niche offers valuable insights as to whether your offerings are already what they seek or if there is a need for modifications. It helps to improve the relationship between your business and clientele.

Improve performance efficiency

Enhancing overall business performance can seem daunting. A better performance implies a better brand-client relationship. Industry mapping saves you from the struggle. You can acquire comprehensive data surrounding the current market position and the factors hindering your brand’s growth. With this information, you can optimize efforts to foster efficiency with ease.

Customer retention

Client retention is an important ingredient for business expansion. You may have attracted the ideal customer base, but retaining them determines your brand’s lifetime value. Industry mapping helps you look into the untapped market segments and find the unmet customer needs. When you know the solution they are seeking, it becomes easier to deliver the perfect offering they are likely to select.

How to implement Industry Mapping

Following these steps will align your brand with the industry’s dynamics and help you drive your business forward.

Step 1: Define your industry

You begin by clearly identifying the industry sector and performing a deep analysis. In this step, the focus is defining the products or services of the region—whether local, national, or global.

Step 2: Gather information

Data is the backbone of an effective mapping strategy that steers the wheel of your business. Procuring data related to the market, competitors, and trends can work to your advantage. Assimilate relevant information, such as industry reports, market research firms, government publications, and trade associations. Research the market size, growth trends, key players, and regulatory influences to get a comprehensive view.

Step 3: Identify market trends

Keeping an eye on the market trends works like a catalyst to remaining aligned with the latest technologies. You become acquainted with the latest happenings in the industry and which technology can be leveraged for your brand’s growth. While figuring out the market trends, also pay attention to consumer preferences. Look closely at the market patterns by evaluating competitors, their market shares, competitive strategies, strengths, and weaknesses. Such an insight gives a clear picture of how your business performs relative to the key players in the domain.

Step 5: Use frameworks for analysis

The framework here refers to an impactful approach like the SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) or Porter’s Five Forces (threat of new entrants, bargaining power of buyers and suppliers, threat of substitutes, industry rivalry). Having a robust framework is a good idea for evaluating competitive forces and building strategic positioning.

Step 6: Determine the opportunities and threats

Discovering opportunities opens doorways to expanding your knowledge base of emerging markets or gaps in the industry. Moreover, it also filters information on threats like new competitors or changes in regulatory compliance. Evaluating these factors churns the wheels of strategic planning.

Step 7: Predict future trends

Anticipating future industry trends can propel your stance in the market dynamics. In this step, consider technological advancements, shifts in consumer behavior, and regulatory changes that could impact your business.

Step 8: Interpret and recommend

Draw from your conclusions and findings. A gist of the insights helps you develop strategic recommendations for your business. Utilize this information to capitalize on the opportunities and address potential risks within the industry.

Summing up

Industry mapping involves steps that walk you through the holistic landscape of the market specific to your brand. Integrating this framework allows you to examine several factors influencing your industry domain, market growth, key competitors, and trends. Though the guidelines we have prepared build the foundation, what differentiates a good analysis from an ordinary one, is the approach.

A structured approach is the key to effectively navigating through the competition. Industry mapping helps you systematically conduct market research, observe the market trends, evaluate the key players, and identify your brand’s strengths and gaps. By analyzing the market opportunities and possible risks, you can plan strategies that maximize opportunities and minimize threats.

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Blogs

The Integral Role of Cloud, AI, and Edge Computing in the Digital Landscape

The Integral Role of Cloud, AI, and Edge Computing in the Digital Landscape

AI, Cloud, and Edge computing has changed our economy. Is the future of computing ambiguous or brighter than ever?

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The width and breadth of human knowledge have been ingrained in the pages of our computational systems.

Our world has changed since Turing broke the enigma and created one himself: his devices, the Turing machines. These computers worked on mechanical rules, but Turing hoped, one day, they might become like us.

Does that future seem far ahead to you? It is a relevant question today. This cyberscape of knowledge, entertainment, and organizational growth. We have leveraged our computation to educate us and survive. Though survive sounds like the wrong word, we have learned to thrive because of our computational powers.

We have collected the sum of our brains and posted them online for all to see. We create actionable data that drives business and predicts events before they happen.

Computation is the closest thing we have to magic. From simulations that mimic life with frightening detail to creating a machine with its brain, it is magical to see how far we have come.

And still, the internet and data grow in its vastness, and with AI-computing, edge, cloud, and especially quantum computing, it feels like we have barely begun to understand what computing can do for us.

Computing is the power to run complex objects for our benefit.

What is Computing?

There are various complex definitions of computing. Ranging from its days as analog machines to the transition to digital.

In essence, computing is the specific set of calculations done by a machine. These machines are Personal Computers, Smartphones, tablets, servers, ARMs and more. There is an endless list of computing machines in the modern world. In 2021 alone, there were 15 billion mobile devices. The number is projected to increase.

Computing is everywhere. From powering our nuclear plants to running a vacuum cleaner, almost everything has a digital chip that carries out instructions beneficial to us.

What are the different types of computing?

There is a vast number of computing methods available to us. Every computing method has its own use cases and wishes to push the boundaries of what is physically possible.

In this piece, we will talk about AI, Edge, and Cloud computing for the sake of business. Let us also touch on some fascinating forms: –

  • Cloud Computing: The Cloud is a bunch of computers called servers that hold vast amounts of data and computational power. These machines are built on scalability or to provide power and data as needed. The servers of a cloud computing system access the internet and stream computational power where required. You can access data and computing power from anywhere, usually subscription-based. There are three types of cloud computing.
    • SaaS (Software-as-a-Service): Provides software/applications remotely to individuals and businesses. Examples: SEMrush, Notion, Adobe Creative Cloud.
    • PaaS (Platform-as-a-Service): PaaS provides enterprises/individuals platforms to build their applications. These usually have various services attached to them, like computing data and storage. Examples: Google Cloud, AWS Elastic Beanstalk, and Microsoft Azure.
    • IaaS (Infrastructure-as-a-Service): Provides only the hardware part of the computation. In short, it provides computational power through its servers, storage, and networking capabilities.
  • Edge Computing: Edge Computing is a tricky one to understand. All definitions say it is the placement of the data generator close (physical proximity) to the data processing plant. It moves data processing from cloud computers to something closer to the source. There are three terms we must understand.
    • Edge Devices: Edge devices process and generate data at the edge. These can range from small devices to huge in-house servers.
    • Edge Networks: The edge networks connect devices and the cloud to allow a seamless flow of information.
    • Edge Applications: These applications are created to run on edge devices. They are low-latency and require minimal connectivity. Example: The software on your home lock or Bluetooth speakers in your car.
  • AI Computing: AI computing is a system that learns through machine learning. It takes vast datasets to derive insights and create outputs based on user requirements. AI computing is revolutionary for its capabilities of changing how we interact with machines in general. There are also types of AI computing. They are based on the methods the AI uses to understand data. Here are some listed below: –
    • Machine Learning: The most popular type of AI computing, machine learning, is feeding the AI large amounts of data sets through dynamic algorithms that help the machine learn.
    • Neural Network: Neural networks are fascinating on their own. Here is IBM’s in-depth article! These networks are models that mimic our neurons’ behavior. An input is given to the nodes, which process it by weighing the options and providing an input. What makes neural networks so fascinating is the concept of the black box. We, the developers of these machines, are still unclear about how they behave.
    • Deep Learning: Deep Learning is a subset of machine learning inspired by the human brain. It uses multilayered neural networks to emulate the mind and enable the machine to do various tasks simultaneously. For example: Recognizing speech and giving a response. Deep learning enables the machine to self-learn and extrapolate new data. This makes them perfect for image and speech recognition.
    • Expert Systems: These are machines that simulate the behavior of domain experts. They acquire knowledge and use this knowledge where their expertise is needed. Expert systems have a rule system to tell the machine to use its expertise in specific ways. They are used as assistants, which increases efficiency. Examples: Legal AI systems and Medical AI devices.
    • Genetic Algorithms: These algorithms behave on the principles of natural selection or the behavior of natural systems. These algorithms aim to cut problem-solving time by mimicking nature’s efficiency. Irrelevant problems are eliminated, and relevant ones are pushed forward. That is the basic logic of genetic algorithms.

4) Quantum Computing: Quantum computing is often hailed as the supreme evolution of computing itself. Basic computing is made up of two logical systems called 1/0. On or off, by combining and recombining these two, our computers operate and carry out calculations.
But quantum computing does away with this and uses the rules of superposition, which says that multiple states exist simultaneously at the same time until observed. Through entanglement— these states called qubits become linked and perform calculations faster than is imaginable.

5) High-Powered Computing: HPCs or high-powered computing performs complex tasks in seconds that take average PCs thousands of hours. It works on the method of parallel processing. Many processors work on the same complex problem in parallel. Example: Simulations, Drug Discovery, and AI Training require HPCs.

The list continues to grow, but when we think of computing, we generally think of these five processes.

Especially, AI, Cloud, and Edge for their vast potential for economic impact. While some welcome the change, others are apprehensive of our overreliance on these systems.

Computing has changed the course of the world. Yet, for many, the direction today seems ambiguous.

We sit at the edge of yet another revolution. Our systems are getting more efficient at what they are doing, surpassing human expertise.

Yet, many dream of a dystopian future where our technology has become a curse rather than a boon. On another spectrum, we feel technology will bring a utopia of unbound human potential.

But as with all technology, our machines may continue to change mundane aspects of life in one way while making it challenging somewhere else.

Especially for businesses, the present and future see AI, cloud, and edge computing play an integral role as they change the digital landscape. And the thing is, these three work in harmony to support each other. Edge computing improves AI, and the cloud improves both edge computing and AI performance.

Edge Computing

The edge has gained traction in the past few years. One look at Google trends, and we understand a shift in the mindsets of enterprises and SMBs alike.

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What happened here? According to Hanover, from 2017, enterprises began to spend upward of $5M on AWS services alone. Now, causation might not be a correlation— we do have to factor in curiosity, but it is something to think about.

And then, there are loading and speed times. Edge computing is necessary for IoT devices. They thrive in low-latency and quick data analysis times.

Edge computing has become popular because of the increasing processing times needed for the cloud and the cost of maintaining the systems. Edge computing has increased the efficiency of factories and retail stores away from Data Centers.

One of the vital advantages edge computing offers is its scalable models. As needed, businesses can add and remove devices from their infrastructure.

Let us take an example of edge computing changing the digital and physical landscape. Think of your smartwatch— it is an edge device. It elevates the digital landscape by analyzing your metrics and providing comprehensive reports on your heart rate, your steps, and a lot more. It does all that within that tiny device, providing data in real time and at high speeds.

Gartner predicts by 2025, 75% of computing will be decentralized. That is, outside a traditional cloud infrastructure. As edge computing takes hold, there are certain security risks identified with it.

  1.  As edge computing grows, it becomes more vulnerable by having more nodes.
  2.  Cost and management, the saving grace of edge, can explode because of the increasing number of micro-data centers in a growing operation.

As the edge takes hold, it is necessary to understand these risks.

Cloud Computing

In 2002, Amazon introduced AWS to help developers integrate Amazon.com unique features in their web solutions. This was free of charge.

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Then, in 2006, the cloud race started with the pay-to-go models of Amazonʼs EC2 that introduced the IaaS model, shaping computing history. Businesses could now rent computational power without buying the infrastructure needed for it.

Cloud computing has made scaling an organization possible. It might be its finest achievement. It does all the heavy lifting for organizations, helping them focus on boosting their productivity and saving time. Cloud has permeated everywhere. From B2B industries to horticulture, every vertical has benefitted from the creation of the cloud.

Cloud provides the building blocks for computational power. And now it sits at a pivotal juncture of its lifecycle—supporting the AI revolution and SaaS development.

Not every business is Meta or OpenAI, but every company wants to leverage the powers of AI without the high cost of maintaining an HPC. Cloud helps reduce the costs associated with AI development.

Every business has begun creating its own AI, from complex machines that store vast amounts of data to specialized tools for helping industry leaders automate their work. And this started with the rise of SaaS.

Cloud computing enables industries to create and deploy software worldwide. No extra hardware is required, just a stable internet connection. With SaaS, technologists can share their solutions through a model-based or tiered-based subscription model. SaaS models have helped businesses save time, money, and operation costs, transforming the industry forever.

Shareable, scalable, flexible, and secure— cloud computing will remain a vital computing power for the future.

AI Computing

Artificial Intelligence is the next revolutionary tech. Today, AI models are helping us make sense of our data. It understands the data by analyzing it with repetition. And observing the patterns that may not be otherwise apparent.

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Since the dawn of computation, we have tried creating a machine that will mimic us. And in the past few years, that possibility has seemed likelier than ever. AI computing is automation.

Automating physical and mental tasks that otherwise would be considered mundane has become the job of our AI systems. Now, AI goes as far as to detect cancer in its early stages.

The future of AI makes computation more than calculations. It transforms computation into the creation of new. Whether creating videos through creative prompts or finding data insights for monetization, AI has begun doing all tasks mechanically possible and some more.

AI has disrupted the world at large. AI computing poses countless advantages but two risks (actually a lot, but with two, we can present a distilled view).

  1. It has the potential to create accurate depictions of false events (Videos, images, audio)
  2. We perceive it to be a threat to our status quo.

Today, AI makes automation of tasks a breeze, but tomorrow, will they do the work of a CEO?

Computing with AI presents us with new opportunities. An infinite canvas with which we can do potentially infinite things. With regulations and compliance, it can be a tool as powerful as humans harnessing fire.

Cloud, Edge, and AI computing affect the digital landscape and transform our physical world.

Computation takes center stage in our modern world. We help it run our electric grids, power systems, and the internet. Even our stock market is electronic.

Our world is a web of interconnected computation. And to make it work, we have created virtual machines and data centers to manage it all for us. The question ‘Where will it take us? ʼ has many answers. From the space race and creative marketing to improving our healthcare systems.

Computation will end up changing the digital landscape and our physical world.

The question is: Will it be for the better?

High-Cost-of-Low-Quality-Leads
Blogs

The High Cost of Low-Quality Leads: A Risk Assessment for Marketing.

The High Cost of Low-Quality Leads: A Risk Assessment for Marketing.

Accurate data is the most valuable resource of all, and it is the basis of lead generation. A successful campaign has one commonality: The data is correct and up to date.

Lead generation requires understanding the campaign and the ideal customer. However, the lead gen cycle has become complex in response to the competitive market. Sales take time to see success, and many leads are not qualifiable. HubSpot’s Sales 2024 report says as much— sales teams are disheartened with the quality of leads.

Attracting and qualifying the relevant leads seems to be the problem for marketing teams.

Marketing teams have to do more with less. The current trend of B2B lead generation has fallen into a vicious loop. Businesses delegate to capture high-quality data to come up with a solution.

This data is based on the specifications and requirements of a particular campaign. How do businesses ensure their message is consistently delivered to relevant leads? By working with the right partners who understand their needs, and the granular approach to lead generation.

This granular approach is based on understanding the nuances of the B2B buying committee and their risk aversion behavior. According to Gartner, a B2B buying process involves six to ten members from different fields and their unique agendas.

Lead generation is dynamic. It is no longer based on a single decision-maker. The buying affects the whole organization, and stakeholders are equally liable for the decision, increasing the risk factor.

Generating low-quality leads impacts communication, and there is a waste of time and energy. This directly affects the ROI. Lead generation should begin by identifying and nurturing each account with specialized content to determine the correct fit. And Ciente excels at changing lead generation from numbers to a strategic game.

Lead Generation is changing, and the market standard has pivoted to become benefit-driven.

What is lead generation?

Lead generation is identifying, attracting, and engaging with individuals or accounts that are the target of a marketing campaign.

Each campaign and the necessary leads are different from industry to industry. These are the specifications of the lead generation campaign.

The goal is to nurture these leads into qualified opportunities for sales.

How is lead generation changing?

Sharon Drew Morgan writes an exceptional piece on how buyers do not buy when there is a need; they buy when they need to mitigate risk. The buying decision is based on how well the software/product can be integrated into the system without disturbing the status quo too much.

Lead generation has changed because lead-to-sales-funnel behavior has changed. It is now risk-averse,

The pandemic, especially post-pandemic was a wake-up call for decision-makers. They need solutions to mitigate their risks, and lead generation should not be to identify the needy but to identify and attract the accounts looking to lessen their risk through solutions available in the market.

Time and again, marketing teams have realized that the market does not know what it wants. Demand Generation exists to raise a hidden problem in question and then bring an answer to it.

Similarly, lead generation must start with the campaign message firmly in place. And that can happen only when marketers understand the problem and the risk by market research and analyzing the existing solutions.

In this case, the availability of high-quality leads is a risk factor. The risk is a waste of time by the sales teams and negative brand perceptions.

Finding relevant leads from the noise requires the harmony of many strategies coming together.

How to discover relevant leads from the noise?

Lead generation must start with attraction. 39% of marketers believe they could improve their marketing with access to better data.

Data Enrichment

Data is elusive. Much of it can get lost or dry because it is not updated. At Ciente, we ensure that data is always fresh and retains its high-quality attribution through our data enrichment services.

Data Enrichment is essential to have a complete view of the leads. By having a complete view: –

  1. Marketers understand accurate lead behavior, paving the way for more successful campaigns.
  2. And the intent signals high-quality leads exhibit?

Data is a game changer and helps mitigate the risks associated with lead gen by connecting relevant parties and paves the way for understanding lead-brand behavior.

Understanding lead behavior

The behavior of a lead is crucial in understanding their intent. Intent data, fueled by data enrichment, gives a multi-dimensional picture of the lead. Helping marketing teams cater to their (the leads’) needs and grasp what they are looking for.

  1. What is the ideal behavior of a high-quality lead?
  2. Where are they viewing their content?
  3. Are they looking for a solution or window shopping for now?

Identifying the behavior of the lead will provide crucial insights into these metrics.

Which will help marketing teams craft the message.

Crafting the right message

Content marketing at all stages of the funnel has become vital. It is a crucial lead nurturing tool. But a message must resonate with the right audience. It should speak to them by understanding the state their industry is in, addressing their problem, and providing a unique solution.

Simon Sinek calls it the Golden Circle Model; it is how leaders are shaped.

By giving the

  1. Why
  2. How
  3. And What

In that order.

This framework helps marketing teams understand their unique proposition and message. As Simon Sinek says, people buy why you do it, not what you do.

Content Syndication

Ciente believes that content syndication is a vital aspect of lead generation. Every organization must invest in this strategy. It helps deliver quality backlinks and boost thought leadership by sharing content to be seen by relevant eyes.

Content Syndication shows the content to as many relevant eyes as possible. When prospects understand that a solution to their unique problem exists and does not disturb the status-quo too m, they will engage with a brand and research more.

Landing Pages

A compelling lead generation strategy requires a landing page. Landing pages are crucial to building email lists and a subscriber base.

With a sleek and focused page, marketing teams can enhance their message, provide value as lead magnets, and get value in return. (The leads’ contact information). This information implies contact consent.

The bullseye for lead gen efforts.

Email Marketing

Email marketing is the king of lead generation and for a reason. It is the most used channel, with a towering ROI of 42:1.

At Ciente, our email marketing team is a robust and efficient success that provides the right content to the relevant accounts at the right time. Email marketing generates leads and nurtures them through a systematic process.

Lead Nurturing

Lead Nurturing is an ongoing process that ensures brand reputation and quality of leads. Nurturing leads is a great filter. It helps qualify relevant leads and disqualify leads who do not show much interest.

It also builds a relationship of trust between organizations. Accounts buy to mitigate risk will buy for trust.

Example: Between Windows or Linux, what will an organization choose for their systems? They will choose the one they trust the most and have consistently shown it can work for their environment.

It is not a matter of choice but of trust between the involved parties.

Demand Generation

The market is continually evolving. Products are rising and failing. How can lead generation ensure success before it starts? In a competitive landscape, it is by finding a unique proposition and creating a demand for it.

Demand generation ensures penetration in the market and the creation of one where it did not exist. This happens by making the relevant market-fits aware of the risk their industry is facing and solving that risk.

The risk of low-quality leads is unacceptable. That is why a new model must emerge for long-term success.

The risk of low-quality leads

Businesses lose $20,000 for low-quality leads the sales team receives.

That is an unacceptable loss for marketers. Marketing teams and CMOs are already on a tight budget and asked to do more with less.

High-quality leads are an increasing rarity. And they must be captured by addressing the risks and identifying the market fits that are looking to mitigate them.

Capture the Category Entry Points of the ideal lead.

The B2B LinkedIn Institute is a subject for deep study. They paired up with the Ehrenberg-Bass Institute for their groundbreaking studies.

One such study is the CEP or the category entry points. These points are memories inside the lead. They say before searching on a search engine, consumers search their brains for answers. Almost every time, leads will go for a safe and dependable partner.

LinkedIn Institute says to market to the 95% out-market prospects and the 5% in-market.

The strategy ensures a steady flow of long-term solutions through awareness and trust building.

Mitigation of risk is where Ciente shines. We create a compelling and cohesive message for your brand.

Our lead generation process combines the dependability of old-school practices with a new granular approach.

The risk factors in the industry are concerning, but understanding why they exist and creating plans to tackle them is the new role of lead generation.

We understand the risks of the market and aim to subdue them with strategic processes, cohesive data flow and compelling messages. This includes keeping our data fresh and up-to-date and generating relevant leads that lead to more sales success.