5 ways to make voice technology work for your business

The future of voice and its impact on customer success, experience and engagement is one you need to start working on, and fast.

As part of #ColliderPredicts, our latest series of events exploring the most cutting edge tech and how that can, and should impact your innovation, we started with voice, and what that could mean to you.

Collaborating with Unruly and their incredible Connected Home, we were joined by voices from Amazon, Matchbox Mobile and Barclays to discuss the next steps for corporate innovation where this is concerned.

Here’s our top five moves we think you could start working on now, thanks to one hell of a special panel* and a room full of high flying corporates who are already thinking “what next?”

1. Offer something substantial.

Voice will be successful for your corporate if you offer real value, otherwise you’ll risk diluting its proposition as a meaningful engagement.

Work out where you can find that meaning for your audience.

2. Don’t offer in isolation.

Avoid becoming too obsessive with voice being the next cool but weird thing — look at it as just another platform like Instagram was to Facebook.

Going forwards, your strategy needs to include voice, but not just voice. It’s another channel to tap into.

3. Get your business prepared early.

Don’t wait until you need to include voice within your strategy. Get the backend of your tech ready to integrate, even before you’re ready to use it.

4. Remember the interaction will be different

The user interface and experience with voice is entirely different to the majority of other technologies we currently use on a day-to-day basis. That means you can expect a different kind of interaction.

Think about how that could impact you.

5. Honesty and TRUST matters.

For voice to be truly successful, we need to have trust in the technology — especially as our homes are incredibly sacred spaces.

It’s up to the businesses using voice in innovative ways to make sure these experiences are truly valuable, and not just there for the sake of it.

*With thanks to: Simon Gosling, Futurist, Unruly Matthew Calamatta, CTO, Matchbox Mobile Chris Chabot, Technology Evangelist, Amazon John Cooper, VP of Mobile Payments Innovation, Barclays Andy Tait, Co-Founder and COO, Collider

And a huge thank you to Unruly Media for hosting us in their incredible Connected Home. What a space.

The Class of 2016 MadTech Applications

As Collider has become a stead-fast part of the London innovation industry, we've seen incredible growth in the numbers and quality of applications year on year. And this year topped them all to date. With 262 from 43 different countries for the next best of MadTech, it's fantastically rewarding to be at the epicentre of the MadTech revolution.

From these 262, 25 were shortlisted to prepare and present to the Collider Class of 2016 Investors - the people who would be making the decisions on who would be joining the programme. From there, we have chosen the lucky few to come to London for a four-month intensive programme, access to senior brand and agency executives and everything the London ecosystem has to offer.

We've highlighted some of the key takeaways from the applications in an interactive infographic below (roll your mouse over any of the graphs for numbers and additional info). Here you'll find our own MadTech categories, location of the companies who applied, and a few trends pulled from the data;

- We are seeing a turn away from content generation startups, as they slide into the third most popular category, to startups focussing on personalisation, advocacy and making content social (clickable, shareable etc).

- Marketplaces and the sharing economy still dominate in Europe with the largest number of application coming from there

- Israel & Western Europe had the most iBeacon applicants

Class of 2016 Insights Create your own infographics

Collider completes £1M Investment into Class of 2015 Startups

Collider, the leading MadTech Accelerator in London, completes their Class of 2015 investment with a second round of £550,000 into six of the most promising marketing and adtech (also known as MadTech) startups from the Collider Class of 2015. After Collider’s Class of 2015 Demo Day at the end of April, these startups were hand-picked by the individual investors to receive up to £100,000 follow-on funding as part of the Collider Accelerator programme. They will now participate in a further 8-month long programme. This is geared towards high growth and preparing the founders to raise a late seed to Series A funding round in 2016. This programme will focus on getting the startups initial traction through commercial trials and deals.

Rose Lewis, Co-Founder of Collider says; “We have found a gap in startup funding which exists between seed and Series A. This is where a significant number of startups fail. This second round of funding will give these amazing MadTech startups the runway they need to gain the necessary traction to raise series A more quickly.”

These six companies have founders from around the world including; Israel, Slovenia, the UK, USA, Australia, Hungary who have all chosen the UK as their company headquarters. The startups solve enduring problems big brands and agencies face on the customer journey including; brick-and-mortar retail analytics, short form video, tracking ‘dark social’ sharing and targeted mobile advertising.

The six selected startups:

[one_third] [/one_third] Brandvee is an audience development platform for media brands that finds, tracks and targets the most influential customers who drive conversion.

[one_third][/one_third] Burst makes big data from little videos and have built the world’s first social video analytics platform which helps organisations understand how to spend more effectively on short-form video.

[one_third][/one_third] Pixoneye  uses people’s photos and videos that they have stored on their mobile devices in order to extract very clever data about them, completely anonymously. By understanding the user through their photos we are able to serve the right ad to the right user no matter what app they are using!

[one_third][/one_third] Real Life Analytics enables targeted advertising on any digital screen. Using patented visual recognition technology we can enable every screen to recognise who is in front of it and serve them exactly the right targeted content in milliseconds.

[one_third][/one_third] Storesense interprets customer journeys in traditional brick-and-mortar stores using passive Wi-Fi. Our advanced proprietary algorithms drive actionable retail advice – from low traffic zone warnings and optimal in-store advertising position suggestions to the best locations for resting areas.

[one_third][/one_third] SyncSpot harnesses the power of entertainment to move people by offering exclusive content that can only be accessed once a customer is at a specific location.

From Moment.us to Preceptiv: A Pivotal Journey

** This is a guest post from Andrew Ko, Co-Founder of Preceptiv **

Pivoting. The very definition means to turn on or around a central point, and this is what we did as a business. Our central point was the idea that useful insights for companies could be extracted from people’s music listening behaviours. This main idea has never changed since the beginning of our journey. However, the way we went about it before our pivot is completely different to how we are going about it now. Let me explain...

The company started out with the BIG IDEA of revolutionizing the way advertising was experienced and consumed. This concept got us into the Collider programme in London and jump started our road to the 'Billion Pound' idea. We created our own free streaming music app (no ads or subscription fee) with the hopes of gaining traction rapidly and attracting advertisers onto our platform.

Describing our music player in a nutshell, it displayed other people’s “moments” (hence our first company name: Moment.Us) with the song you were currently listening to so that you can experience what they experienced when they were listening to that same song. This created a more social and connected music listening experience and was a fun way to discover new music socially, an idea that I still hope gets implemented in the future by one of the larger players (ie. Spotify, Google, etc). The app was also beautiful, which was usually the first thing a new user would tell us. It was iOS 7 flat design before iOS 7 was released by Apple. So we thought we had everything tied down: the concept, the platform and the music licenses. Now all we needed was to convince brands to start putting their ads in there and we’d be in business because, I mean, how hard could it possibly be to attract a million users to our platform while giving away free full-length songs?

But what was that saying again? “The best laid plans of mice and men often go awry”. Yeah, that’s what happened to us. It wasn’t for lack of trying though, as our team did its very best to make it a success. But when we approached brands or advertisers, we ran into a few problems. The three most common were:

1. They wouldn’t get on board without the user numbers
2. They wanted to see proof that it worked before they committed
3. They wouldn’t pay for the music royalties

We essentially ran into the 'chicken-and-egg' scenario in which we couldn’t get advertisers on board if we didn’t have enormous amounts of traction, but we wouldn’t be able to pay for the amount of music we were giving away unless we had revenue coming from the advertisers.

We also learned that giving away free music didn’t help sell the app (trying to buy word-of-mouth advertising) and that we actually needed money for marketing.

The numbers our app generated told a two-sided story:

In terms of user numbers to appease brands and get them on board, it was quite small. We managed to attract around 3000 users from the UK on word-of-mouth marketing as our app was limited to UK iOS users only (due to music license and resource restrictions).

However, in terms of engagement numbers, it was through the roof (higher than Facebook sponsored posts) and people found this way of music discovery extremely enjoyable.

Based on the feedback we received, we knew that our concept of using music to connect people was solid but the way we delivered it was just too expensive for anyone to buy into. So now what?

We had to pivot fast as we were running out of time and money. So we took our special sauce (our knowledge in connecting music with people’s experiences), threw out the delivery mechanism (the streaming music app) and started over again.

Music + Personality

We knew that our strength was linking music to people’s behaviours, experiences and identities so we decided to start there.

One of the key elements that people liked about our app was using music to determine someone’s state of mind. But what if we could also use music to determine not just someone’s state of mind at a particular time, but also their personality overall. This was actually a part of my PhD research; how music can be used to figure out people’s identities or personalities. The reason being that there really is nothing more personal than the music we listen to.

Armed with this new idea (and a new name: Preceptiv), we set off to verify that we could build such an engine. Drawing on previous academic research in this field, our mission was to turn raw quantitative music listening data into rich, insightful qualitative data that can be used to profile people’s personalities.

Why personalities you ask? Because we looked at the current state of the customer analytics market and they only profile users in two-dimensions - demographics and behaviours. However, the key to our technology is that it enables companies to profile their customers in three-dimensions by adding the key missing variable: psychometrics. This additional signal informs companies the motivations behind their customers’ actions and enables them to take the appropriate action to increase engagement, conversion and loyalty.

I’ll give you a very simple example: If Expedia knew that Joe (who’s 35 and lives in San Francisco) recently took a trip to Vietnam and they wanted to recommend him other places to visit, they’d probably suggest other trips to Southeast Asia just based on the fact that he went to Vietnam but not knowing what he did while he was there. However, if Expedia also knew that Joe is the adventurous type and likes thrills (because of his personality type), they could also send him more relevant and meaningful recommendations such as a safari trip to Africa or a volcano hiking excursion in Hawaii (which is closer to home for him). It’s been scientifically proven that a key aspect of what drives us through life and motivates our actions is through our personality. Being able to tap into this insight is incredibly powerful, and to do it on mobile devices (instead of solely on the web) is a dream for most companies.

This is actually what our secret sauce is all about and why we’re extremely excited about our pivot. We’ve cracked how to gather all of this data on mobile devices in seconds, with the same accuracy as a 50-question personality test, and without the user having to provide any input manually. It only takes minutes to harness the power of our technology, as its just a simple SDK being dropped into a mobile app. However, we realize that music is subjective so we need to continue collecting data, testing and refining our model in order to provide as accurate a view about people’s personalities as possible.

And that’s what we’re doing right now. Once we prove this works, there are a whole range of applications and companies that could benefit from the results of our experiment (we’re currently targeting the retail, financial and travel verticals). We’ve had great responses so far, trialling the technology with a few companies and getting useful feedback to refine our model. But we’re not done yet. All of this work is required for our journey towards the holy grail of startups: product / market fit. It’s taken us quite a while to get to this point, with a lot of twists and turns, but it’s definitely been worth it.