Conversational experience

Users exploring data expect to interact with a series of questions and answers, as well as to use intents meaningful for to their business context. Datagramar chatbot framework allows to build experiences relevant for each business

Real conversations with a virtual data analyst

Optimised experience

Datagramar is designed with a subtle mix of natural-language interactions, menu-based engagement and interactive charting to achieve the right balance between simplicity for the end-user and effectiveness in the data exploration process

Guided onboarding

To break the ice, the chatbot welcomes first-time users with a straightforward onboarding that explains how to use the service and what kind of data analytics is available. This initial flow can be tailored and enriched for each business and even each user

Smalltalk

Users love small talks. Datagramar is capable of handling chitchat conversations to make conversations more natural. Small talk is entirely configurable so you can even make it specific to your business

Designed for non-data savvy users

Datagramar puts a particular emphasis on the service experience. Because the solution targets non-technical not used to deal with data analytics, the experience has been built to overcome the challenges around:

The complexity of expressing and formulating questions related to data
The lack of understanding and literacy required to make sense of the results

3 data exploration paths

I'm lucky

Similar to the well-known Google Search ‘I feel lucky’ option, the assistant randomly presents responses to a pre-configured set of questions. It is usually the preferred option chosen by users discovering Datagramar service for the first time

Explore

A guided mode based on menu interactions where the user is asked to answer step by step specific questions helps him formulate a complete request of data exploration.

Help

Information on the amount of knowledge the chatbot can offer and details of the data it has been trained on. Users can easily understand the exploration criteria available to them (like metrics and dimensions)

Frequently Asked Questions

The ‘explore’ path sequentially asks the user for:

The KPIs to explore (e.g. ‘sales & discount’)
The dimension to segmente by (e.g. ‘by day or by shop’)
Any applicable filters (e.g. ‘for Madrid’)
The temporal range of the data (e.g. ‘of last week’)

The conversational flows are built on a fully customisable state-machine engine. This means that you can transform the standard onboarding or exploration flows to create ad-hoc conversations that fit your needs

Yes. Datagramar conversational state-machine and BLP engine are fully customisable, meaning Datagram can perform any custom actions you want (like creating a support ticket or interacting with a CRM or ERP system)

Yes. Users can interact with Datagramar via text or via voice. When the interaction happens over voice, the chatbot will respond with text and graphs as well as voice (by speaking the chart title or the response).