whenwhyhow is a pioneer product in the space of digital customer service. Whenwhyhow allows:
- Modelling & structuring customer data creating a Customer Data Platform (CDP) built on top of NoSQL database.
- Whenwhyhow introduces a new type of mindset-behavioral analytics based on crossing customer actions with external events looking for the whyes, whens and hows, potential causalities and create behavioral profiles able to generate hyperpersonalization through your digital channels to improve engagement and loyalty.
- Customer-journey analytics, which provides insights about usage of digital channels and trendy Chatbots & Voice Assistants.
- A brand new use case of AI/ML, providing customization patterns and enables empathy generation within the digital channels. The focus is the customer engagement improvement while other AI cases focuses on NLP or recommendation (short-term upselling).
- It also covers customer events indirect known by banks/fintechs as payments or PSD2 aggregation in order to analyze behaviors and potential usage of channels or external triggers related to those events.
NO! whenwhyhow is integrated with your customer service channels or well at integration level in the case of conversational channels (chatbots or voice assitants) or at "summary session" level reporting the metrics you defined as useful for mindset-analytics (let's say app or web visited screens, particular action performed or not, etc.)
NO! whenwhyhow is an Customer Data Platform integrated with your CRM to import customer info including the segmentation information (full or partial). In the same way that whenwhyhow uses CRM information as the segmentation whenwhyhow can provide new types of segmentations detected by user behavioral patterns enriching the CRM data.
However, in case of not having CRM already deployed in your IT architecture the segmentation capability of whenwhyhow can serve as CRM-lite.
The segmentation of customers could have a few comment segments (age, language, education level, location, generalistic client-tier) but lots of particular segmentation possibilities related to the specific vertical in which the enterprise operates. I.e. Airlines could segmentate the customer according to the number of flights taken, percentage of delays suffered, seat preferences while banks could add additional classification on wealth, income, mortgage status, types of investment, etc. Then, the whenwhyhow platform web tool allows to easily define the segmentation needed for your company and also try with different tiering o segments.
The privacy of the end-customer data is key and whenwhyhouse philosophy is to identify the customer record as a code that only knows the enterprise, pseudonymisation, and could be different from personal public identifiers. It allows to deploy the solution in public clouds without sensitive personal information.
An external context is whatever phenomena that could potentially impact in the customer behaviour modifying the probability of a customer-care interaction. Each enterprise using Anbotux could easily define an external context (example: its own stock evolution) and assignining daily a value (ordinal from bad to good) as a way to normalize whatever context in a similar way to apply Statistics/AI/ML techniques.
You may see a video explaining this topic
whenwhyhouse is using a NoSQL database, MongoDB, as it matches the needs of the platforms and has been accreditted in many potential customers as Banks, Airlines, Insurance companies, telcos, etc in order to easy the licensing with full support of database.
whenwhyhow offers a set of 4 HTTP Restful APIs to feed the platform with the data: 1) conversational-channels API to be used by the company/team in charge of the conversationa channels to introduce all the chatting events and also getting user-feedback for personalization. 2) Customer Data API to be used by customer departments to migrate the customer data from CRM needed for a proper segmentation and analysis. 3) Non-conversational channels summary sessions API to be used by customer care department to load the history of access via whatever channel as starting point to evaluate the chatbot impact along the time. 4) External Context API to be used by enterprise data scientist or external providers to create normalized datasets describing and measuring a myriad of different phenomena. The reason to offer this as 4 APIs with different APIkey is because we gather 4 types of data with different owners in each enterprise, the logical approach is that each "data owner" only can feed the platform the data she/he is responsable for. The API manager used is WS2O by it could be replaced to other used by enterprise customers upon request.
The initial features include:
- Conversational & not converational channel metrics collection and visualization.
- API accessible user profile including channel-mix, channel-mix evolution, conversational skills & external context reactivities and segment-benchmark mapping the customer-mindset.
- Data feeding APIs (Customer Info, conversational interactions, non-conversational channels summary sessions & External Contexts API).
- Customer segment enterprise defined configuration.
- Digital channels enterprise defined configuration.
- External contexts to be evaluated enterprise defined.
- Chatbot/Conversational A/B agnostic testing (chatbot vendor independent).
- New UX Look&Feel based on VUE technology.
- Cloud based offering.
- API exposure using WS2O.
- Customer-Journey analytics.
- Machine Learning external context impact evaluation on customer-segments and individual users
- Intent flow converational agnostic visual analysis to detect bottlenecks & conversational flows design mistakes.
- SaaS version. (available as sandbox for prospect customer & partners).
whenwhyhow is offered as a product/service combination with a setup fee and a monthly rate to help with the integration and consultancy about potential use cases and the inmediate deployment of new features being developed according to the roadmap. This way also allows to create a collaborative roadmap prioritization according with additional needs collected by the initial customers.
Initially the production pricing range varies from 0,25 to 1 € /year per end-customer analyzed in database. The range is depending on enterprise providing their own cloud and/or database/API Manager licenses or everything provided by whenwhyhow.
PoC & Trials are provided with a pricing affordable for innovation departments.
Whenwhyhow can be deployed in Google Cloud Platform (GCP), Amazon Web Services (AWS) and Azure.
Currently we are not offering SaaS but the platform is SaaS ready and we are planning a SaaS model in Q2'2021 to extend the benefits of using whenwhyhow to SMEs and big companies prefering an easy try & buy mechanish to evaluate the solution.
Suppose I am a chatbot/voice assistant developer or framework, an IVR vendor, or an IT integrator in the space of customer care and/or business intelligence /data analytics, could I resell whenwhyhow to offer a more complete solution for my customers?
Yes, whenwhyhow is actively looking for partnerships with chatbot/digital channels or CRM companies as initially we opted for not reinventing the wheel and focus to extend the possibilities of digital channels (helping to analyze better the end-customer base and helping to create better personalization) with a cooperative approach.
We are offering a competitive margin for partners.
Supposing that a messaging app or a telco for its RCS "MaaP" initiative would like to offer whenwhyhow capabilities as cloud based tool for enterprises using his messaging channel to create chatbots, may we partner with whenwhyhow to offer this tools for our enterprise customer base?
Yes, of course, whenwhyhow is eager to partner with messaging apps and telcos launching RCS Business Messaging to offer cloud based customer intelligenge / AI VAS tools for enterprises.