Everything that your business engages in is ultimately for your customers. Having a customer-centric approach where you analyze your customers, helps to genuinely understand their motivations.
The aim is to identify customer needs and expectations, through customer feedback and the insights they offer. And not through intuition, but through data-based Customer Needs Analysis. The insights will enable you to align your products and services with your customers’ needs and expectations, and deliver significant customer value.
Understanding the customers’ needs will enable you to design better products, offer personalized services, and connect with them better. In this article, you will get insights into customer needs analysis, types of needs, and how to effectively analyze them to influence business decisions.
A structured and data-based method for identifying a customer’s needs for a product or service is called customer needs analysis. Product and brand managers use it for various reasons, including concept development, product development, Value Analysis, and Means-End Analysis. A customer needs assessment reveals what customers need, how those needs are (or are not) being met, and how one can improve satisfaction and loyalty.
Understanding your customers; such as their spending power, pain points, quality expectations, and more, allows you to evaluate whether an idea can be implemented feasibly. Customer understanding enables making changes in the early stages and helps develop action plans that maximize your chances of product adoption and achieving long-term success in the market.
Customers almost always leave reviews, both good and bad. This is an incredible opportunity for you to understand what they liked and what they didn’t, and be able to cater to them better. Your product may be best-in-class, but if your purchase process or return policies are complicated, customers may be willing to choose a competitor with better service.
Gather all sorts of customer data from surveys, product reviews, social media, and online forums. Conducting Market Opportunity Analysis leveraging this data will enable you to identify new opportunities to innovate, improve, and remedy any factor compromising your brand.
Understanding customer needs through data-backed evidence, paves the way for you to deliver an exceptional customer experience at every stage of the buyer’s journey. So, what are some of the needs to be cognizant of?
Customers have certain expectations from the product they want to purchase and specific requirements they want it to meet when shopping for it. Customers’ needs drive their purchasing decisions, so various factors motivate them to buy a product. In most cases, businesses will encounter the following customer needs:
Throughout the entire customer journey, from first contact to last, the customer experience (CX) is cumulative. It builds over time. It may consist of live chat, messaging, navigating a website, switching between touchpoints, talking to an agent, or receiving ongoing support as they use a product, service, or offer. Customers’ perceptions of a brand will be formed based on each of those engagements, ultimately determining whether they remain loyal to the brand.
Surveys are usually sent to respondents to obtain their input on customer needs analysis. There is a lot of emphasis on questions concerning a brand’s competitors and product awareness in these surveys. The data used in this analysis can assist companies in identifying their target customers’ needs and assessing their market position.
With the help of the following practices, businesses can conduct effective customer needs analysis.
Combine the data collected through direct questionnaires with all customer-related information collected from CRM systems and customer service departments to gain a deeper understanding of the results.
The data captured by contact centers can be extracted for analysis, examined, and compared to industry averages for metrics such as customer satisfaction (CSAT) and Net Promoter Scores (NPS).
Identifying opportunities for improving engagement comes from businesses that understand how their consumers find their brands and how they interact with their products. Maps of the customer journey provide executives with a visual representation of how customers encounter their products and services.
Customers’ search patterns on search engines will indicate what types of searches should lead to the organization appearing in page rankings. The search terms and questions users ask search engines vary depending on the stage of their customer journey. A brand’s positioning within these situations can measure its alignment with customer needs.
Customers’ feedback about your brand, products, and services is referred to as the voice of the customer. Analyzing, capturing, and interpreting the voice of the customer is known as the voice of the customer analysis.
Surveys, interviews, social media, and other methods are well-known ways in which brands obtain customer feedback. Taking it all in and making sense of it is the real challenge. Brands can understand their customers’ needs and wants using a market research technique called the voice of the customer.
Your natural language needs to be processed with the help of Natural Language Processing, or NLP. The system that analyzes the voice of customer data must be capable of sifting through all of the data and understanding the information. Through the analysis of the words, it will be possible to identify trends, customer preferences, topics, and issues.
Analyzing text and speech data allow you to gain insight into customer-agent conversations. Insights such as these highlight areas for improvement, recognition, and concern, so that customers and employees can be better understood and served.
With Speech & Text Analytics, you can improve your customer service experience with a variety of AI-powered features. Automated speech-to-text conversion simplifies customer interaction analysis by converting audio recordings into text. You can determine what matters most to your customers by using speech analytics, which detects emotions and analyzes trends. You can identify problematic conversations by analyzing differences in pitch and tone.
With topic identification, you can categorize calls based on their content and the words and phrases they used most frequently. Root-cause analysis can be applied to call recordings for easy statistical comparison.
The use of Machine Learning (ML) accelerates and improves the efficiency of textual analysis. This can reduce labor costs while accelerating processing time without compromising quality.
As soon as you have an experience with a brand or are satisfied with a product or service, it would be best if you gathered feedback. Regardless of how well the survey is constructed, the respondent is still being asked to recall past experiences or circumstances.
Gathering as much unsolicited feedback as possible is crucial. Companies can valuably uncover customers’ perceptions of products, services, and levels of support through social media listening. Additionally, reviewing review sites will enable you to gain a better understanding of not only the brand but the industry or sector in which it operates as well.
All collected data is classified based on primary physical and psychological customer needs in the processing stage of the customer needs analysis. Further refinement can be achieved by aligning the data with identified customer archetypes. Next is to identify common keywords, positive and negative emotions, and customer journey steps using an analysis.
A well-analyzed set of data should tell a compelling story. A detailed or compressed analysis will not make sense if it fails to compel customer needs or is challenging to grasp. A clear and accessible visual representation of data from a customer needs analysis will assist stakeholders in buying into the project.
Customers choose products based on value-driven goals determined by a means-end approach. In this process, you analyze customer responses to assess why a particular customer would purchase your product or service.
An analysis of means-ends identifies interconnections between three areas of customer interaction. Features and attributes of the product are the first areas to consider. Secondly, the product’s real and perceived benefits should be considered. Lastly, for the third area, the unique qualities of the customer will be considered. This enables them to experience those underlying benefits, including functional, physical, financial, social, and psychological ones.
Your organization may not currently have access to all the tools and expertise needed to effectively analyze your customers and generate actionable insights. This is where analytics outsourcing comes into play. An analytics partner such as Course5 Intelligence can provide you access to the required talent and the requisite solutions, and deliver actionable consumer insights in near real-time.
When it comes to retaining and rewarding your customers, it all comes down to how well you know them, and their trust in you. But since every customer is their own individual, you need to be able to analyze them at an individual level and as segments, to be able to personalize the content they consume, the products/services they purchase, and the experiences they have.
With our end-to-end customer analytics solutions, you can enable Customer Journey Analytics to help you map the customer journey across touchpoints and understand customer needs and pain points. This opens the door for AI-powered segmentation and personalization solutions to help you deliver a better customer experience at every stage of the journey.
Customer retention and risk-modeling analysis are also available to help you identify which customer segments are likely to churn and their reasons for it. You can also understand which campaigns and experiences contribute towards retention. Now you can further customize customer experiences with customer experience analytics, to increase retention and impact ROI.
An active lead propensity model can be used to continuously monitor customer lifecycle value (CLV). Based on the Account Risk and Insights Scorecard, low-potential customers and upsell opportunities can be identified.
Course5’s graph-based approach creates a faster time-to-value. The purpose of graph databases is to store, map, analyze, and traverse networks of connected data, and provide insight into invisible contexts and synergies between customers and the products they buy. It also analyzes the data to find personalized recommendations with low latency.
What’s more, you can access all your customer data and insights through a unified Customer Data Platform. A standardized solution for single customer views, to better understand customers and influence business decisions.
The client, a leading multi-national tech company, wanted Course5 to support its SMB transformation by leveraging segmentation and advanced analytics to identify qualified customers from high-growth industries. Then target those customers based on their share of the wallet and propensity to convert.
We built a single-view Customer Profile by assembling data from all touchpoints and channels, and created customer segments based on behavior and preferences. Our RAD models and CDP were able to identify high-value segments, helping the client personalize online product recommendations based on the industry size and type. This was with the aim of enabling the targeted campaigns to drive an uplift in subscriptions.
Testing revealed a 38% increase in customer registrations, a 2.1% conversion rate increase and an 8.6% RPU lift all of which contributed to the SMB business growing from $0 to $1B in two years.
As the outcome of Course5 end-to-end analytics support, we coached and enabled the organization to accelerate the growth of SMB business, with 15% savings in media spending. Moreover, there was a 48% revenue realization from first-time buyers in AP markets from RAD-based campaigns; and a 9pt increase in registration rate post our suggestion to direct traffic to specific pages through paid programs.
Leveraging Knowledge Graphs to accelerate customer 360 with connected insights. In this approach, we identify factors that can be connected to provide a personalized customer experience, through a tailored journey applicable to both B2B and B2C business models.
In our approach, we are able to capture interactions between people and services over time and form a network to be naturally analyzed with graph queries. With support for flexible schemas and arbitrary relationships, graph databases are a great place to store and analyze data from multiple kinds of database systems – from relational to document to key/value. Each can be represented and queried as nodes in a graph.
The impact delivered, helped reduce floor time, and call center time debugging complex customer problems and recommending relevant products.
Customer retention and attracting new customers play an integral role in the success of any organization, regardless of size. Hence, understanding your customers’ motivations, challenges, desires, and goals is essential to offering them true value and an exceptional experience.
A new generation of customers has arrived with new expectations and behaviors, affected by emerging trends and disrupted markets. That’s why a customer needs analysis needs to become integral to your business and your business decisions. Keep learning about your customers’ needs, adapt to their requirements, and continue to remain competitive.
And if you ever need help, don’t forget to reach out to us at Course5 Intelligence.
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