Oct

Amazing Social Data for Travel Companies

                                                   

A huge number of travel related conversations is happening every day on social networks.

Based on nmodes Twitter data (averaged over 1.5 years of observations) there is

- 1 conversation every 15 minutes in which people notify that they are going to NYC;

- 1 conversation every 43 minutes in which people from the USA express intent to go to Europe;

- 1 conversation every 4 minutes with interest or intent to go on vacation;

- 1 conversation every 3 hours in which people are asking for hotel recommendations.

And this is just a tip of the iceberg.

(nmodes currently has 70+ travel-related topics and intents, and growing.)

For travel companies all these are qualified leads, potential customers, and attentive audience.

Reaching out to these potential customers results in a positive consumer experience, brand recognition, and, yes, sales!

Interested in reading more? Check out our other blogs:

AI unmasked: Have chatbots failed?

It is becoming increasingly popular to say that chatbots have failed and are overhyped.

While it is true that in many cases expectations from chatbots significantly exceed the results on the ground, the anticipation of chatbots’ demise are somewhat premature. 

One of the main problems for chatbots is that the market is inundated with low quality solution providers who deliver low quality results. This happened because conversational AI seems to have low entry barriers. Unlike other recent technological darlings such as space technology or renewable energy, conversational AI is purely software and therefore does not require vast sums of initial investment. 

What this approach is missing however,  is that conversational AI, in addition to being a software, also requires an accurate understanding of how language works. And there is a limited number of people in the world that do have such understanding.

When conversational AI is delivered by AI experts who understand the way human language works, the results are good and convincing, just as how you would expect them to be.

Suffering from unsatisfactory product quality is a common problem for many new and emerging industries.  The rules of the market dictate that most of the low quality players will eventually disappear. Poorly created chatbots will therefore not be around for too long.

READ MORE

Beware the lure of crowdsourced data

Crowdsourced data can often be inconsistent, messy or downright wrong 

We all like something for nothing, that’s why open source software is so popular. (It’s also why the Pirate  Bay exists). But sometimes things that seem too good to be true are just that. 

Repustate is in the text analytics game which means we needs lots and lots of data to model certain  characteristics of written text. We need common words, grammar constructs, human-annotated corpora  of text etc. to make our various language models work as quickly and as well as they do. 

We recently embarked on the next phase of our text analytics adventure: semantic analysis. Semantic  analysis the process of taking arbitrary text and assigning meaning to the individual, relevant components.  For example, being able to identify “apple” as a fruit in the sentence “I went apple picking yesterday” but to  identify “Apple’ the company when saying “I can’t wait for the new Apple product announcement” (note:  even though I used title case for the latter example, casing should not matter)

READ MORE