After 8 years on the telco consultancy business, two senior executives of nae (one of the leading telco consultancy firms in Spain) decided to put “their money where their mouth was” and develop technology targeted to measure and enhance customer experience of mobile services, as they saw no other company understood how to address this need.
Based on our experience, we figured out that small actions on key elements along the value chain can produce great benefits to improve the experience of the customers, requiring low investments and producing great tangible and intangible benefits.
One year later, and already serving major mobile and fixed operators in Spain, we founded case delivering customer experience enhancing products that reduce costs, increase revenues, promote loyalty and drive new revenue streams.
Crazy about technology, always taking new challenges, native problem solver. Engineer, double Masters degree, Executive MBA.
Objective focused, project driven, always thinking new ways to reach the clients. Engineer, executive MBA.
Math genius with love for sports. Can create a prediction model while playing football. Telco Engineer.
The UI guy. More than interfaces, he creates experiences for the user. Data visualization master. Computer Science.
QoS is her middle name. Perfectionist, client oriented. focused on delivery and positivity. Telco Engineer.
MapReduce wizzard, crunches databases for breakfast. Industrial Engineer.
Passionate about wireless technology and motor sports, coder by nature. Telco Engineer.
Challenge solver, creator of improvement opportunities, database guru. Computer Science.
Embedded systems enthusiast, information society native and sports fan. Computer Science.
Prediction guru, Big Data expert and music enthusiast. Computer Science.
We believe in solving problems by combining our experience, our deep understanding of the client and some ingenuity to add perspective.
We approach challenges by applying a 3 stage method using the latest technologies and creative business models, delivering common sense products adjusted to the reality of the problem to solve.
By applying fast prototyping techniques we are able to create an hypothesis of how to solve the problem and a first working version of the solution within weeks, delivering tangible proof of the viability of the solution proposed.
We turn proof of concepts to production level applications, creating stand alone products that solve precise problems without adding complexity (and high costs).
We provide or customers with the choice of using our products as services built around flexible business models in line with their needs, taking care of the a wide range of activities and providing an end to end solution.
We created PREDinten as a prediction engine, with or without internal data, that correlates social network and online activity to real life actions such as attending a venue, buying a product, voting for a candidate or watching a TV program, among other activities.
PREDinten solves the problem of adjusting the offer to fulfill the demand without overdimensioning (loosing profits) or undersizing (loosing clients).
We understand that either shortage or wastage of resources when addressing the demands of customers often results in poor customer experience, which in turn leads to higher costs, lower profits and fewer customers.
Predicting demand to adjust offer is a common practice that ofter fails to provide results as most companies relay on internal historical information, basically building their models in the same factors that drove them to provide an inaccurate offering.
We believe that prediction must take into account external information to understand the customer and its intention in its own terms.
PREDinten analyzes social media activity identifying individual streams of conversational information, establishing patterns of real life intentions.
Each stream is classified according the type of intention, allowing us to identify if it is related to attending an event, purchasing a product or service, voting for a candidate, etc.
Classified intentions are geolocated and grouped according to their proximity, locating the impact of the intention with an actual address or longitude and latitude reference.
Geolocated intentions are tracked and measured constantly to provide a prediction of the volume of customers foreseen to actually carrying on with their intention.
Predictions turn into alerts to inform about the estimated change in demand, allowing our clients to act with plenty of time to adjust their offer and provide benefits to their customers as well as reduce costs, improve their image, etc.
Advanced data analysis features enable PREDinten to provide a complete service, from identifying and predicting changes in the demand, to estimating the cost/benefits of adjusting the offer, providing clear and precise information for the decision makers.
Up until now, customer perceived quality and technical measured quality were as different as apple and bananas, and even knowing that they hold little relationship, company wide budgets are thrown to reduce these gaps.
MEDUX is a geolocated customer experience measurement, prediction and analysis product for fixed and mobile networks (2/3/4G, WiFi, CDMA), providing for the first time ever an objective score of the user perceived quality, delivering a single view of the service offered for both business and technical decision makers.
Telco operators across the world constantly measure their customer satisfaction with surveys and their technical quality with drive testing and signaling and traffic data evaluation. Even when these tasks have been part of the business since the beginning, the results for each measure have little to non relation, making difficult the task of assigning resources to improve customer satisfaction.
The subjective nature of the customer perceived quality, where the opinion can be influenced by external factors such as brand reputation, billing period, terminal longevity, user technical knowledge or even customer location, makes very difficult to spot the real status of the service delivered. This subjectivity forces operators to invest on improvement of the perceived quality without certainty of what and where to fix to make customers happy (and drive revenue up, reduce churn, improve margins, etc.)
We believe that measuring customer experience with an objective approach, while collecting technical data, provides a bridge between the perceived and technical quality, as well as the directives on where and what to change or fix on the different elements of the network. This objective approach helps operators focus their limited resources into specific key points of enhancement with guarantee return in terms of O&M savings, targeted sales, better customer experience, loyalty and overall quality improvement.