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Voice of Customer (VoC) B2B Marketing in 2024

Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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90% of marketers state that marketing efforts should be more aligned with customer needs.1 However, only 24% of marketers always implement customer feedback data in their decision-making processes, and among those, 55% are not happy with the quality of data.23 This results in widening the gap between companies and the customers as their voice does not reach decision-makers.

In this article, we explore how B2B companies can use the voice of customer insights in their decision-making processes to help them navigate in an ever-changing business environment.

What is voice of customer (VoC) data?

Voice of customer (VOC) data is a type of feedback that is collected directly from customers. It is a way to learn about the thoughts, opinions, and attitudes of the customer base generally, as well as with regard to a company’s products or services, and it can be used to increase customer satisfaction and loyalty.

Voice of customer data involves but not limited to customers’:

  • purchase history
  • personal preferences (e.g., communication channels)
  • historical browsing data

Companies primarily use customer surveys to collect VoC data, followed by focus groups (e.g., customer interviews), speech and text analytics (See Figure 1).

Source: Gartner

Figure 1. Preferences of B2B companies in measuring voice of customers

How to use the voice of customer insights in B2B marketing?

1- Optimize communication channels

Businesses can learn which communication channels their target customers prefer and how they use them by examining VOC data. For instance, if a company’s target market is primarily active on LinkedIn, it can concentrate on developing its LinkedIn presence and engaging with clients there.

Businesses can more readily contact their target customers by optimizing their communication channels, such as website design, search engine optimization (SEO), social media, and email marketing.

2- Create targeted content

Source: Content Marketing Institute

Figure 2. Content types B2B marketers used in the last year

44% of marketers state that most of their marketing budget goes to content development.4 VOC data can provide insights into the topics and themes that are most relevant and interesting to customers. This information can be used to create targeted content such as blog posts, whitepapers, webinars, and more. By tailoring the content to the specific needs and interests of the target audience, companies can improve engagement and build thought leadership in their industry.

Read our article to learn more about B2B content writing challenges and solutions.

3- Tailor personalized companies or incentives

Businesses can create customized offers or incentives by using the insights they get from analyzing VOC data to better understand the particular needs, preferences, and pain points of their customers.

For instance, businesses can use VOC findings to customize free trials or demos, increasing the possibility that users would find the product or service helpful and convert to paying customers.

4- Refine brand image

Companies can collect customer feedback and analyze the data to understand how their customers perceive their brand and identify areas for improvement. This information can be used to refine the company’s brand image, including:

  • messaging
  • tone of voice
  • visual identity. 

By ensuring that the brand image aligns with the needs and preferences of the target audience, companies can build stronger connections with their customers.

5- Improve customer experience

Research shows that 90% of B2B buyers would turn to a competitor if a supplier’s digital channel couldn’t keep up with their needs, and 48% of buyers said finding up-to-date product or service information was a top challenge.5

By analyzing VOC data, companies can identify common issues and pain points in the customer experience and take steps to address them (See Figure 3 for an example). By satisfying customer expectations, companies can increase customer loyalty and satisfaction, customer retention, and build a stronger reputation in the marketplace.

Source: Marketing Charts

Figure 3. The most influential purchasing decisions of B2B buyers

6- Discover potential markets

VOC data can provide insights into the needs and pain points of different customer segments, which can be used to identify potential markets and new growth opportunities. For example, if a company’s existing customers are primarily in one industry, VOC data can be used to identify other industries with similar needs and pain points, and tailor marketing efforts to those segments.

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Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Sources:

AIMultiple.com Traffic Analytics, Ranking & Audience, Similarweb.
Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
Data management barriers to AI success, Deloitte.
Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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