Customer experience measurement

Assess your customers' experience to know how to improve it

Consultancy and technology to assess the entire Customer Journey. We identify your customers’ friction points to improve every interaction (Touchpoint), basing your decisions on data.

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client experience Custom experience surveys Official Bain license Real-time data

Hundreds of companies trust Openmet

Advisory services in design, methodology, assessment, diagnosis, and action plan

Customer experience encompasses the different emotions, perceptions, and opinions that customers feel and hold throughout their interactions with your company. To assess the customer experience, definitions of the following elements are typically used, which we can help you define:
 

  • Customer journey: a visual or chronological map of all the interactions, whatever they may be, that customers have with the company, describing their perceptions and emotions throughout the journey
  • Touchpoints or moments of truth: a detailed description of each of the interactions with products, services, websites, etc. that the customer experiences throughout the Customer Journey
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Results

Assess your customers' experience to redesign it, build loyalty, and gain competitiveness

An excellent and personalized experience

We assess the aspects that affect the customer experience and identify the improvement points and critical areas to redesign and personalize it.

Data-driven decisions

We work with KPIs, metrics, and objective indicators such as NPS® (Net Promoter® Score) to make decisions backed by data.

Greater loyalty and competitiveness

We identify what builds customer loyalty and strengthen the company’s competitiveness and advantages.

How we work

Advisory, assessment, diagnosis, and action plan for the customer experience assessment

We support you throughout the entire process with our own technology and strategic consultancy.

1

Advisory and methodology

Our customer experience experts advise you on the methodology, the process to follow, and the system for obtaining customer feedback.

2

Multi-channel, quantitative, and/or qualitative surveys

We manage the research using the most suitable channel in each case: customer interviews, electronic surveys, phone surveys, SMS, on-site interviewers, QR codes, in-depth interviews, or focus groups, among others.

3

Openmet Feedback Manager results platform

You have Openmet Feedback Manager at your disposal to view and analyze customer feedback in a Business Intelligence environment and create all kinds of reports there.

4

Analysis and presentation of results

If you wish, our consultants analyze and present the assessment results to you, identifying strengths and areas for improvement so you know how to enhance the customer experience.

5

Action plan and follow-up

If you wish, we help you build a concrete improvement plan and provide you with goal management software to roll out and track each action.

Access the Openmet Feedback Manager demo

To help you better understand what a customer experience survey is, request the demo. You’ll receive a sample survey by email and access to the Openmet Feedback Manager environment to review the results obtained.

Request the demo

OFFICIAL NPS

Official Bain license to work with NPS

We are one of the few companies in the world certified by Bain & Company to apply the Net Promoter Score (NPS) methodology.

  • Certified methodology.

Your partner

Why Openmet?
You need a partner, not just software

20+ years of real-world experience

Over two decades helping companies across every sector understand and improve their relationship with their customers.

500+ companies vouch for us

The trust of hundreds of clients certifies the strength and reliability of our methodology.

Proprietary technology

Business Intelligence software to analyze results and make data-driven decisions.

Expert guidance

More than a platform. We're a consultancy specialized in customer experience that helps you execute and measure every improvement.

AI-augmented consultancy

More time with you, less spent on document production. We let artificial intelligence work in the background so we can focus where we add value.
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TESTIMONIALS

What do the clients who trust Openmet say?

Working with Openmet on our annual customer satisfaction survey is synonymous with success. We would like to highlight their high level of professionalism, their speed of execution, and their excellent service quality, which allow us to make strategic decisions.

Miguel Barajas Production Director

Start assessing your customers' experience today to increase your customer loyalty.






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    News, tools, techniques, and advice on customer satisfaction and experience

    electronic customer surveys

    Electronic customer surveys: Asking more with fewer questions

    In our day-to-day work as a firm that conducts customer satisfaction and experience projects and surveys, we often come across the same dilemma: We want to ask and find out lots of details about our customers… But we can’t ask everything we’d like to because the survey would be too long (which would lead to other problems such as abandonment, poor quality responses and increased costs, among others) Electronic customer surveys. In this post, we outline three basic strategies that we use in customer surveys to solve this problem at least in part and achieve what may otherwise seem impossible: ask more with fewer questions. Three basic strategies for asking more with fewer questions in electronic surveys 1. Pre-segmentation This strategy could alternatively be called “Never ask what you already know”. Although it may seem obvious, many customer surveys and forms do not heed this rule and ask customers about aspects that are already in the company databases. This should never happen. A good survey should pre-load this data to make it available during the survey and results analysis and not pass on to customers the internal data management shortcomings of the company. Generally, two typologies of customer are surveyed: A. “Known” customers (or B2B customers, on whom we already have information in the CRM or other data sources). These customers are in the company database and we probably already have information on aspects such as: The name of the customer or their address The area where they live or the store where they usually buy The type of products or services that the customer purchases Their annual revenue or classification in the customer ABC The sales channel they use … and many others B. “Unknown” customers (or B2C customers, anonymous customers, such as customers who go to a restaurant chain or visit a website). Although these customers are not in the databases, it is also possible to pre-segment them using information that we may already have, such as the geographical area or establishment where the survey is conducted. We can also obtain automatic information on customers through other means, including the use of social WiFi (the customer gets free wireless access in exchange for sharing details of their social profile).   2. Conditional questions and answers We could also call this strategy “Don’t ask what doesn’t concern you”. The aim is to make sure – based on the responses and customer data we already have – that all the questions asked of a customer are relevant and can be answered. To adapt the survey to the customer profile, we need to use conditional questions and answers, hiding and showing whole parts of the customer satisfaction survey based on the information we already have. For example, if we have preloaded customer data, we can ask only about the specific product or service that we know they use. The ultimate aim is to ensure that all of our questions are relevant and can be answered by the customer and that we are not wasting our “shots” (or questions) unnecessarily.   3. Random questions This strategy could also be called “Divide and conquer” or “Jigsaw survey”. The idea is to divide the survey into parts as small as we would like so that each customer only answers a few questions. The questions will be different for each customer. This system allows us to obtain aggregate results (responses from all customers) with data on answers to lots of questions, but with partial samples for each. In other words, we can design a survey that is as complex as we like provided that our sample is large enough to be divided into small parts that can be selected at random to minimize any bias (most survey software incorporate this option).   Conclusion Typically, a good satisfaction survey design gives us far more information on customers – both their characteristics and their opinions – without having to answer to tiresome questionnaires. Three possible strategies are: pre-segmentation conditional questions random questions With these strategies we can achieve the seemingly impossible: ask more with fewer questions.   […]Read More… from Customer experience measurement
    Satisfacción clientes encuestas

    Satisfaction surveys: How to choose the most suitable type for each case

    When our clients ask for help with their projects to assess customer satisfaction or experience, there is one important aspect that needs to be decided from the word “Go” because it will dictate certain features of the study: the decision on how and which is the best system for conducting interviews or customer satisfaction surveys. Telephone? Face to face? Electronic? This decision is typically made based on different reasons that we wish to summarize in this blog post. Satisfaction survey: types of customer surveys and interviews The tools available for obtaining feedback or interviewing customers generally end up being one of the three types shown in the table below. Each type of satisfaction survey has its pros and cons that we will need to evaluate based on the characteristics, aims and budget of the study. Type of survey Pros Cons Most common applications Face to face · The survey can be done on the spot, at the same time as the product or service is consumed · High cost · Key customer surveys · The required sample can be selected dynamically and in situ · If customers are geographically disperse, it is more expensive · Surveys with more qualitative information · Objects or information can be shown directly to the customer · Takes longer to complete · Long, complex surveys · Good answers to open questions · Surveys where the customers are together in a single place and time · The customer can be asked to complete certain aspects · On-the-spot surveys at the point of service By telephone · We can have a lot of control over the interview content and exact process · Average cost · All types of general survey · The selection of the right sample can be very good · It can be boring if lots of similar questions need to be answered (e.g. with scoring scales) · Some customers may be difficult to find · Visual information cannot be displayed Electronic/Web · Low cost · Low indexes of response · B2B surveys with a strong or fixed relationship with the customer · A large number of or all the customers can be surveyed · There is nobody to clarify questions · Surveys to users of websites, cell phones or apps · Customers can respond when it suits them · The answers to open questions tend to be poor · Surveys integrated with business software (CRM, sales outlet, reception, etc.) · Video and images can be inserted · Subsequent statistical processing may be needed for the selection of the correct sample · Internal satisfaction surveys to company staff · Easy to answer and usually quick for customers · Automated, regular, very short or unassisted surveys (e.g. newsstands) · Studies are quick to conduct To find out more about satisfaction surveys, we recommend reading other articles from our blog here. […]Read More… from Customer experience measurement
    customer satisfaction billing

    Customer satisfaction and revenue weighting analysis

    Most of the studies on customer experience and customer satisfaction surveys that we do at OpenMet typically include an analysis weighting the results by revenues. This post will briefly explain this type of analysis of results and its main features. What is revenue weighting? Briefly, revenue weighting is a way to analyze customer results by magnifying the results of the customers giving the greatest revenues and minimizing the results of those with the least. The main reason for using revenue weighting is that companies typically look to target the needs of their most profitable customers with their action plans and strategies, thereby obtaining greater profits and turnover. When we use weighting, the indicators of customer satisfaction or metrics on customer experience will change (sometimes very significantly), so our conclusions will be much more representative of the real importance of each customer for the company. Let’s look at an example using the classic Pareto principle: if a company obtains 80% of its turnover from 20% of its customers, the opinions of this more lucrative 20% of its customers will logically have a greater weight in the indicators of satisfaction or loyalty. If we use the usual method (e.g. arithmetic means) to analyze customer responses, the responses of this 20% will be diluted by the 80% of the other customers. The upshot is that we will have a customer satisfaction indicator in our scorecard that doesn’t really fit in with the company’s priorities. How does revenue weighting work? The most common solution is to change all calculations of results to use weighted averages. To choose the weighting to apply to each customer taking part in the survey, OpenMet basically uses two strategies: 1.Strict weighting: the revenue from each customer is used as the weighting. This system works well when there are small differences in revenues from each customer. By contrast, when the revenue of some customers is huge compared to others (e.g. several customers invoice millions of Euros, while lots of others invoice just a few thousand), the system poses problems because the opinions of smaller customers are virtually eliminated from the average due to their low relative weight. 2.ABC weighting: weighting is done by associating a relative weight to groups of customers, for example, based on the typical ABC grouping (or similar). The weight assigned to each customer depends on the weight assigned to its group. The weight of each group of customers is decided externally by taking into account the priorities of the company (e.g. A customers weighting = 10, B customers weighting = 3, C customers weighting = 1). This strategy gives good results in some cases, such as when strategy 1 is not suitable. However, it can be difficult to assign weights because the weight of the group is somewhat arbitrary. Conclusion The weighting of results by revenue is very important for a good analysis of customer satisfaction or experience. It gives us indicators and metrics that offer a truer picture of the company and allows us to reach better conclusions and define action plans more precisely. More information on Customer Satisfaction. […]Read More… from Customer experience measurement
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