Archive for the ‘Technology’ Category

The Fourth Industrial Revolution is Business as Usual

November 27th, 2018 by Heather Maloney

the fourth industrial revolution

I work in the industry that has been pronouncing or driving dramatic societal changes for the past 3 decades:

  1. The internet … I remember that catch phrase in the 90s of “if you aren’t on the internet within 12 months your business will be dead”.
  2. The year 2000 bug … stock your pantries, the world is about to end when equipment stops because of the general lack of support for a 4 digit year.
  3. Closely followed by the dot.com crash of the early 2000s caused by speculative, and outlandishly overvalued investments in technology companies.
  4. The internet of things was discussed around 2010 which predicted that within a short period of time all manner of things will be interconnected, utilising the internet, to provide a dramatically different way of living. That more “things” would be connected to the internet than people.

All of the above became kind of true (and the internet of things is still playing out / expanding), but not reaching the zenith proposed by the vendors of the theories; yes, vendors – many of the voices behind these ideas stand to gain by promoting the concepts.

So, it is no surprise that as we approach the end of this decade, my colleagues and others have started talking about the next big dramatic change – the 4th Industrial Revolution (’4IR’). 4IR is fuelled by technologies such as artificial intelligence and machine learning, cloud technologies, and 5G. Many of those discussing 4IR predict the destruction of humanity as robots take over, leading to mass unemployment.

“The fourth industrial revolution is growing out of the third [the digital revolution] but is considered a new era rather than a continuation because of the explosiveness of its development and the disruptiveness of its technologies. According to Professor Klaus Schwab, Founder and Executive Chairman of the World Economic Forum and author of The Fourth Industrial Revolution, the new age is differentiated by the speed of technological breakthroughs, the pervasiveness of scope and the tremendous impact of new systems.”(1) Those talking about 4IR want us to embrace the new technologies and allow humanity to explore them to their fullest extent in order to achieve great improvements in the lives of everyone. Greater sharing of knowledge and resources than ever seen before is key, which in turn requires a new economic model to ensure that every person in the world has their needs met in a fair and equitable way. End environmental degradation, poverty, homelessness, hunger, and provide equitable access to education, nutritious food and significantly advanced medical care.

I listen to talk about 4IR with what I view is a healthy dose of skepticism. I agree that technology will continue to promote and support change at an exponential rate. But when it is all said and done, we are still humans, living our human lives. We naturally more easily understand, and therefore trust, people who are similar to ourselves – whether that’s the language we speak, where we went to school, where we have grown up, the details of our upbringing, our worldview. It is my expectation that moving to a new economic sharing model is the zenith that will never be anywhere near achieved, despite how attractive it may sound. We will not succumb to, or comply with, a small number of organisations controlling all the data and resources, and their distribution. Different groups of people will continue to evolve technologies to solve common problems, in different ways. We are already seeing push back – Google have recently been successfully fined a record 5 billion dollars in Europe for anti-trust. Also in Europe the GDPR legislation is pushing back against the will of corporations such as Google and Facebook to use data at their own discretion, just because they provided a free service when they were gathering that data.

It is my view that we will continue to explore the benefits of new technologies; some will make vast sums of money from new inventions and innovations, some will lose their jobs and need to retrain to do something else, but the vast majority of humans will keep living their lives with a few extra conveniences that modify what used to be the norm, and hopefully improved medical outcomes and a cleaner environment. On the whole we will become more knowledgeable; whether we become wiser remains to be seen.

I also believe that every type of industry will be affected by rapid technological developments. That includes technology companies! We are constantly under pressure to offshore, change technologies to the latest thing, provide services and solutions for very low cost or free. I am careful to not just jump onto the latest bandwagon for ourselves or our clients, but to make sober decisions which appropriately weigh up risks and benefits, and also reflect my personal values.

Change affecting business is nothing new. That’s part of running a business – recognising, adapting to, or taking advantage of the change going on around you is a fundamental skill of a business owner, those responsible for business strategies, and the corporate board.

(1) https://whatis.techtarget.com/definition/fourth-industrial-revolution

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Cloud does not equal the Internet

November 13th, 2018 by Heather Maloney

Cloud does not equal the internet
People frequently use the term “cloud” or “in the cloud” to simply mean located on the internet or their private intranet. I’ve done it myself, for the sake of expedience. However, they aren’t the same thing, and it’s important to understand why so that you can wisely choose the internet services you are accessing for your business or in your personal life. For example, cloud hosting is not the same as shared web hosting, for the hosting of your organisation’s website.

The internet is the connection of computers around the globe using TCP/IP protocol to manage the connections, and participating in the sharing of information using the HTTP protocol (the worldwide web).

The term “Cloud” or “Cloud Computing” refers to technology services, usually delivered over the internet, which are characterised by:

  • Distribution of a system (program and its data) across many servers and locations, to provide for greater performance, but still providing up to date and correct data.
  • Automatic provisioning (addition of greater capacity via more CPUs, memory and disk space) to meet minute-by-minute requirements.

Applications embodying cloud computing are often further labelled as SaaS (software as a service), PaaS (platform as a service), IaaS (infrastructure as a service), and other ‘…aaS’ names. These labels draw attention to which part of the abstraction of the technology is controlled by the buyer compared to the service provider. However, not all applications given these labels actually provide the two main characteristics that I am asserting differentiates cloud computing ? distribution across many servers, and automatic provisioning. Instead, software delivered as a service via logging into a web application may in fact be stored on one server, in one location, with one database, and require the service provider to manually procure and set up new servers when usage demands the additional resources.

The characteristics of cloud technology provide advantages and disadvantages which I will discuss in a moment, but let’s first consider the technological challenge cloud technology is trying to solve.

As you can imagine, there’s an awful lot of information contained within Facebook. Millions of users each adding several posts, and making hundreds of comments, on a daily basis, adds up very, very quickly. Not only is there a lot of data being stored and accessed by users of Facebook, people are posting and reading comments from all around the globe; some on their phones while riding on a train, others are sitting at their desktop computer in the back of beyond, and everything in between. No one will use Facebook if it takes more than a few seconds for the content to appear on their screen, and Facebook is used by people all around the globe. Facebook is just one example of an application which handles vast amounts of data and serves vast numbers of people.

To make Facebook possible, as well as other applications like it, the underlying technology has to be distributed across multiple servers and locations – a distributed system. There are numerous technical models used to achieve a distributed system. Below are brief descriptions of just a few of the techniques to give you a feel for the complexities involved.

Techniques

Sharding. A term allowing a single database to be stored across multiple servers by allocating logical portions of the data onto different servers. A very rudimentary example would be determining which server to store the data based on a range of identifiers such as in the case of user accounts the decision could be made to store all data with a user ID between 1 and 100,000 on server 1, between 100,001 and 200,000 on server 2, and so on. The application retrieving the data would send the query to the application server, and then the database server would work out which server to get the data from based on the user ID, get that data and return it back to the user. There are many options for the way that a database may be divided; the right way for a particular application will need to consider the way current data is spread across it’s attributes as well as how future data may grow.

NOSQL. The example given above for sharding described separation of data contained within a relational database; the most common database architecture up until very recently, which as the name suggests relates tables of information to one another by linking IDs. A person’s record in a database may contain an ID to another table storing the details of the school they attend (name, address, phone number etc) – hence being called a relational database. NOSQL or Document Databases have become more popular recently as they can be spread more easily across multiple servers because all the data associated with the person in the sharding example would be stored in one document rather than spread amongst related tables. Document databases often come with functionality built into them to manage distributing documents in the collection across multiple servers.

Caching. Storing data located near to users, providing faster access particularly for commonly used information is referred to as caching. Facebook makes heavy use of memcache to store recently accessed Facebook information in memory, which is much faster to read than from the Facebook MySQL database which is housed on hundreds of thousands of servers. Content Delivery Networks (‘CDN’) are an example of caching of web content to ensure it is closer to your website visitor.

Other concepts such as virtualization, utility computing, and grid computing are also key in the implementation of cloud computing particularly with regard to auto-provisioning of additional computing resources.

Advantages

We have touched on some of the advantages of cloud computing in relation to the problems it is trying to solve. The advantages can be summarised as:

  • Security. A cloud solution must be focused on security in order to have success over the long term, and they usually have significant resources at the ready to keep security up to date, and respond quickly when a new threat arises. Look for:
    • End-to-end encryption which ensures the encryption of all data in-transit across the Internet and stored at-rest in the cloud, with the encryption keys held by you and used to encrypt the data before it leaves your computer.
    • Sophisticated access controls allowing you to set role-based authentication to control what exact data each user can and cannot view, edit or share.
  • Performance. Because there is likely a server nearby to the user, rather than the user’s request needing to travel half way around the world and back, you can expect the speed of cloud systems to be significantly better. Performance is a key factor for organisations with a workforce distributed around the globe.
  • Scale. The ability to distribute an application and/or its data across multiple servers and locations removes or significantly reduces the constraints on how large an application can grow or how many customers it can efficiently serve.
  • Cost. Another key benefit of cloud is that usually someone else is responsible for concerns such as installation of software and purchase of licenses, management of software patches, backups, hardware upgrades and repairs, anti-virus and protecting against malicious attacks, all handled by the provider of cloud computing rather than the organisation requiring the technology. When comparing the cost of cloud and non-cloud you must take into consideration the total cost of ownership of the alternatives. Auto-scaling (also referred to as elastic computing) is a factor in both cost and performance, as it allows systems to scale up (additional costs) when demand increases, and scale back (reduce costs) when demand is low, allowing the owner of the system to only pay for resources when they are required.

Disadvantages

It is important to also be aware of the potentially significant disadvantages of cloud computing:

  • Data ownership / sovereignty. Where is your data really? Who has access to it? Have you read the terms and conditions with respect to the ownership of the data? Can you remove your data permanently, or will it still be accessible by the cloud provider even after your account is closed? Often the owner of the data you place into a cloud computing solution is actually the cloud provider, not you. To help mitigate this issue, some cloud providers are implementing servers in additional countries including Australia, to help organisations to use cloud services without moving their data overseas, but you need to check where your data is stored; often such storage choice will increase the cost of the solution. NB: even if your data starts out being stored in Australia, if the data is owned by a US company, they may be forced to move the data back to the US for scrutiny by American law enforcement agencies – this has already happened in the case of Google in February 2017.
  • Privacy. Facebook has been criticised at the highest levels of American government, and by governments around the world, for the way in which the data it gathers (albeit via their free service) has been used and sold on to 3rd parties. The situation with Facebook and other cloud solutions has been a factor in leading to the new European privacy legislation (GDPR). When you utilise cloud platforms, are you comfortable with manner in which they use the data that you are storing within it (read their terms and conditions)? Can you trust the organisation to abide by their promises?
  • Control. Can you create the functionality you need to support your particular processes, or are you now constrained by the services provided by the cloud platform? Using a cloud service to remove the need to create that service constrains you to the functionality the service offers. The more you depend on a 3rd party service, the less likely you are to be able to innovate in that area of your business on application, which may well slow your organisation down and remove your opportunity to create competitive advantage.
  • Cost. Whilst being able to pay per second for your application using cloud technologies may sound like it is going to reduce your cost, if your application isn’t built to take advantage of cloud technologies, the opposite may occur and your costs can be significantly more than using simpler internet technologies. Cost can also be significantly greater if you use the wrong technology on the wrong cloud provider. For example, whilst the major suppliers of cloud technology usually allow you to run any type of application on their cloud servers, the cost of running those different types may be very different. Running a MS SQL database on Google Cloud is extremely expensive, for example, compared to running it in the Microsoft Azure platform. You need to choose your technology wisely.
  • Skills. Not everyone developing applications is experienced in working on large scale applications, and the implementation of applications using cloud technologies is relatively new, so finding personnel with the required skills can be very challenging.

Whilst I have primarily been discussing cloud computing from the point of view of building an application such as Facebook, cloud computing underpins solutions such as Office365, DropBox and GSuite. These applications allow users all over the world, sometimes the one person in different parts of the world in one day, to access their data – emails and files for example – and programs such as GSuite and Word Online, with great performance, and without the data being [noticeably] out of date, most of the time. Such applications are also increasingly providing users with the capability to collaborate on files e.g. contributing to an online document simultaneously, again while located in different cities and countries.

For such commodity type applications, where easy access from anywhere, across multiple devices, makes business much easier, the decision to sign up for cloud computing may feel like a no-brainer. But you still need to consider the disadvantages discussed above.

In summary, not all internet applications are using cloud computing technologies. Cloud computing is a complex area, utilising multiple strategies aimed at providing up to date information, to mass users all around the world, with great speed. It is important that you way up the advantages and disadvantages of cloud computing for both your commodity technology needs (email, file sharing, file storage, and other operational systems) as well as when developing your own applications.

If you would like to read more:
https://enterprisersproject.com/article/2017/1/three-things-companies-must-know-about-data-sovereignty-when-moving-cloud
Use of Memcache by Facebook: https://www.usenix.org/system/files/conference/nsdi13/nsdi13-final170_update.pdf

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Digital marketing … for those who started business more than 5 years ago

September 29th, 2018 by Heather Maloney

If you started your business more than 5 years ago, you could be forgiven to believing that online marketing was something to try out if you had a bit of spare marketing budget. Times have changed. Over the last few years, the reality of digital marketing for small business has gone from a nice-to-have to a must-have for most businesses. Consumers are more connected than ever before, and their default behaviour when looking for anything ? products, services or information ? is to grab their mobile phone and search online. Even word of mouth has gone digital; recommendations happen across social media, and online reviews can have a significant impact on your business.

Bottom line: digital marketing is more important now for small business than ever before.

We have many clients for whom we have carried out digital marketing across a wide range of platforms and strategies, many of which achieved significant increases in new business enquiries or sales. Some of our clients now receive the majority of all their incoming work through digital marketing channels.

That’s not to say that word of mouth is unimportant; it’s simply that digital marketing provides you with immediate results and a wider reach at a lower cost.

However, it is very possible to implement digital marketing poorly, and therefore not achieve the results you are seeking. That’s often why we are engaged by our clients to design, write, execute and manage digital marketing for them.

Digital marketing can have a bit of a bad reputation. Unfortunately, there are many less scrupulous service providers who use digital marketing tactics to grow their own business and then fail to deliver tangible results for their clients. Even worse, they use tactics to “game” online platforms like Google for short term gains but ultimately end up with the client being penalised.

At Contactpoint, we take an end-to-end approach to digital solutions for our clients, and digital marketing is just one part of it. It’s our holistic approach that helps us deliver real results for clients, as we take the time to discuss our client’s business needs and only then recommend an approach for digital marketing that can deliver results. We never recommend the latest digital marketing technology just because it’s flavour of the month, nor will we cheat the system to get the quick results.

Just one example of our success in delivering digital marketing results for our clients is Nortan; providers of air conditioning and heating service and installation. Via a range of activities including a great mobile responsive website, pay per click advertising and SEO, Nortan are kept very busy all year round with new incoming leads, and have grown their business significantly over the time we have been providing digital marketing services. In fact, from time-to-time Nortan ask us to pause their digital marketing campaigns, because they are too busy with new work! What a good problem to have!

Nortan heating and cooling services

We work very closely with our clients to ensure that the level of business digital marketing campaigns produce are manageable.

If you would like to revisit your use of digital marketing to grow your business, please feel free to call Heather Maloney for a chat.

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The What and Why of Inbound Marketing

June 26th, 2018 by Heather Maloney

Inbound marketing (aka ‘permission marketing’) refers to the strategy of attracting leads for your business via company-created digital content. That content addresses the needs which your products or services fulfil or problems which they solve, resulting in the right people (those trying to solve that problem or fulfil the identified desire) approaching your organization, and working their way through your material in order to self-select or qualify themselves as a potential customer.

So, inbound marketing is a strategy. You need to assess whether it is a strategy that is suitable for your particular business and marketplace.

Inbound Marketing Strategy

Why Inbound Marketing?

Because everyone hates being sold to … it’s that simple!

When was the last time you were on the end of a cold call, and you thought “oh yes, why not spend the next 15 minutes listening to this offer about why I should switch electricity companies?” And even if you have engaged in such a phone call lately – perhaps to the person from a very worthy charity, rather than the electricity provider – did you end up buying / donating or just wishing them a nice day?

If you are in sales, and you only have to talk to people who are already in the market for your products / services, your job is so much easier.

Inbound marketing the focus is on providing help or value, rather than making a sale. The sale will come as a natural result of providing value and solutions.

Inbound marketing also addresses the new buyer behaviour that we have seen evolve over the last decade; customers carrying out personal research and practically making the decision with regard to what they want to buy, before they ever talk to a vendor. Also, with the proliferation of paid TV, many more free to air channels, internet radio, and free video content, ensuring that a more traditional advertisement is seen or heard is a lot more difficult. This article provides many statistics showing how effective inbound marketing can be compared to outbound marketing.

Please note, I am not saying that traditional marketing no longer works … I heard a presentation from a career telemarketer just last week, explaining the benefits of lead generation via cold sales calls. You need to ensure that your choice of marketing strategy is right for your market and your ideal customers.

Fleshing out your Inbound Marketing Strategy

If you decide that an inbound marketing strategy is right for your organisation, then you need to:

  1. Plan the content you are going to create in order to solve your prospects questions and engage them in their journey of discovery, building trust in your organisation, and desire for your products and services.
  2. Determine which tools or platforms you will use to make your content accessible to prospects.
  3. Create the content!
  4. Disseminate the content and make it easy for people to find, and/or pay for traffic.
  5. Measure and analyse the results, improving the content over time.

Clearly implementing an inbound marketing strategy requires effort and co-ordination of a variety of activities. Utilising a team of resources will help you implement more quickly. Tools such as a content calendar will help you to plan out the creation and distribution of your content in a logical manner.

Which Tools should I use?

Inbound marketing = making your marketing material extremely accessible so that your prospects can easily find the answers to their questions or solve their problems (i.e. find your products or services), when they are actively looking. Your content must add value, and guide prospects for whom your products and services are a good fit, towards the point of purchase. Some people will be in a hurry and will purchase immediately that they find a solution, so being able to buy from any piece of your digital content is important. Other prospects will take their time, evaluate multiple options, test you out, and then finally purchase days, weeks or months down the track. For such buyers, your content needs to educate and build trust.

The following tools are useful in implementing an inbound marketing strategy:

  • Search engine optimisation (‘SEO’) – this activity is very important for ensuring that your digital content ranks above other organisations competing in the same space. Over time you want to “own the topic”, that is, be on the first page of results for every search on relevant words or phrases. SEO obviously needs content in order for search engines to point somewhere. The following types of content will deliver high ranks in the search engines the mostly quickly:
    • Blogs - either a blog on your own website, or blogs published on other popular websites, pointing back to your website.
    • Videos - most commonly distributed via YouTube, giving you access to people searching through this video search engine.
    • Reviews - usually in 3rd party platforms such as Google Reviews. However, they can also take the form of testimonials in your own website, including video reviews.
    • Website content – including online courses, guides, survey results, reports and research, white papers, diagnostic tools.
    • Press releases – often distributed via dedicated PR sites.
  • Pay-per-click advertisements (‘PPC’) – whilst this might sound like traditional outbound marketing, because you can configure your ads to only appear in response to searches for specific keywords or phrases by people located in a particular region, PPC ads can be very useful for bringing visitors to your website who are trying to solve a particular problem. PPC is very useful for bringing in immediate readers of your content while you are waiting for your organic ranks (SEO) to improve. Google Adwords and Bing are the main two platforms for PPC ads, because they are the most used tools for searching for answers to problems. PPC ads must be supported by dedicated content on your website, also called ‘landing pages’. People who click on your ad will arrive on your landing page. To get the best return on your investment in that click (you are paying per click), it is important that the content delivers on the ad, and then takes the visitor along their journey of [hopefully] deciding to buy from you.
  • Social media – people talk about topics on social media, as well as talking about their lives. Find where topics related to your products and services are being discussed, and then get involved in the conversation. Posting your own content in your social media accounts will also help people to find your content when they search for it in the social media platforms ? most social media platforms use hashtags (#) for helping people find content on a particular topic.
  • Social media advertisements – this is PPC within social media platforms. The difference is that for some of the social media platforms, you can configure your ads to only show for people who match very specific demographics.
  • Email and SMS marketing – once people have identified themselves as actively seeking to solve a problem or fulfil a desire, hopefully for your product, they may subscribe to receive future email and SMS messages from you. To inspire visitor opt-in for email / SMS there must be compelling value contained in your digital content. Often your blog content and other website content will be pushed to subscribers in a logical manner.
  • Marketing automation – tools which automatically send a choreographed series of content to subscribe to learn more about your products and services. The more sophisticated of these automation tools will start and stop the delivery of your content, based on the manner in which your prospect is interacting with your content.

One of the great advantages of digital marketing tools is that they enable you to measure the interactions of people with your content, and identify where visitors are dropping off. This can help you to improve your content and marketing process over time, and therefore increase the rate of conversion of visitors to paying customers.

As part of our digital marketing services we would be delighted to help you determine whether an inbound marketing strategy is right for your organization, define and plan your strategy, create the required content, implement, and analyse the results.

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How can Business (big and small) Harness Artificial Intelligence?

April 30th, 2018 by Heather Maloney

Futuristic city with delivery person sending off drones with packages from skyscraper
A recent Contactpoint blog post described the way in which artificial intelligence and machine learning are impacting our world at large and how it works. This blog attempts to answer the question “How can business, both small and large, utilise AI to make significant advancements?” AI is certainly not a technology only available for large corporations.

I assert that there are 3 main ways that your business can benefit from artificial intelligence (‘AI’):

  1. By integrating your website / app with software that has been improved by the use of AI. Such integration will significantly improve the value provided by your solution.
  2. By using software that has been improved by AI for running your business, thus significantly improving the manner in which you run your business, on an ongoing basis.
  3. By running your own deep learning exercises to determine the answer to a difficult question, which either improves your business performance or your understanding of your clients.

I expect that you already, perhaps unknowingly, use the outcome of AI or machine learning every day. Understanding it will help you harness it even more, so let’s explore just a few examples of each of these opportunities.

Integration
The Google search engine is underpinned by the use of AI – the more web pages it crawls, the better and better it gets at providing people with valid and useful search results. That’s part of the benefit of AI; traditional programming requires modification over time in response to the way people use it, with AI driven solutions, they learn and improve on their own.

Baidu, the so-called Chinese version of Google, allows you to upload an image, and request “similar images”. The search for similar images is not based on text around the images on a web page but solely uses the content of the images (2). Images, in technology terms, are made up of pixels of colour, which individually tell you very little. It is the manner in which the colours are combined, and the hard and soft edges around groups of pixels, which determine what is actually represented. AI underpins Baidu’s ability to find similar images – a very complex problem, and probably not something you could program a computer to perform. Traditionally the ability for a programmer to tell a computer how to achieve a goal was a prerequisite to solving that goal programmatically. With the use of AI, instead of telling the computer how to solve the problem, the program is allowed to train itself to solve the problem, getting better and better at achieving a task the more times it is performed.

We all use text search to find the things we need in Google or other search engines. It’s been possible to integrate the Google Search Engine into your website or app for many years, including restricting the search results to a particular domain or set of domains, thus providing excellent search results to your visitors without needing to write a search engine algorithm yourself. The ability to also search by images may be the differentiator that your website or app needs to deepen the value for your customers.

Other AI enriched applications that may enhance your application include:

  • Voice recognition – for speech to text and voice control of your app.
  • Language translation.
  • Image recognition e.g. Facebook suggesting name tags for people in photos you upload.
  • Route planning e.g. navigating from one place to another, taking traffic and other factors into consideration.

Clickup.com, a project management software, provides another example of integration. They announced this month that Clickup is now integrated with Alexa and Google Talk, allowing users to quickly interact with the online software by voice (3).
Google and Microsoft allow you to play with some of their AI enhanced functions via websites (4).

Operations
There are many functions that all businesses carry out. These functions are attracting the application of AI in order to make the tools used to complete these tasks, exponentially better than they have been before, and thereby attract new business.

Keeping up with the last news in your industry during your morning commute is now so much easier thanks to tools such as Voice Aloud which enables your smart phone to read an article to you while you drive (carefully of course). Your smart phone will also allow you to search using voice commands, using Google Voice Assistant or the iPhone Siri, allowing you to search hands free.
I recently asked my Android phone “Okay Google, what do I have on today?” expecting to have a list of my appointments read to me – it did that and, then started playing me 2 – 3 minute snippets of daily news recorded by various news agencies around Australia. It was a fantastic way to keep up-to-date and it “learned” that behaviour all on its own.

Google Search enables you to find relevant information, and this search is very accurate, powered by AI. It’s very important for Google’s revenue from online advertisements that Google Adwords provides relevant ads to searchers, because it is the relevance that inspires people to click on an ad, thus earning Google revenue. Similarly ads which appear in amongst Facebook news feeds are very reliable for showing your ad to the right audience, and once you have achieved excellent click through the result of Facebook’s AI research ensures that it will promote your ad to “look-a-like” audiences, based on what it knows about the people who already clicked. You can now much more confidently spend money on pay-per-click, because you can tailor your ads to specifically targeted audiences.

In a recent Contactpoint blog we talked about chatbots – the best of these are underpinned by AI, improving their results the more they are used so that they can help answer an inbound question before the human gets involved.

A number of online customer service and customer relationship management tools are now underpinned by AI. In these functions AI is bringing valuable insights as you use the tools, such as:
- Which clients are at the greatest risk of leaving you? (5)
- Which phrases and styles of interacting with customers produce the greatest sales results?
- What are the most important additional products or services to provide to your customers?

The better banking and financial management tools are now underpinned by AI to help you identify fraud (6). Similarly computer networks are being better secured from intrusion, viruses and malware now by solutions that use AI to detect unusual behaviour (7).

If your operations involve designing products and engineering, AI is making great inroads into design tools to help speed up the process (12).

Actionable Insights / Solving Problems
So far we have considered AI lead improvements to more general problems. Your business will be operating in a particular domain in which you are an expert, and in which there are very specific problems that have not yet been solved, or can’t be solved quickly & reliably for a large number of customers. This is where the power of AI may be the most potent, because machine learning / deep learning can be used to arrive at breakthroughs in your particular domain. Whilst it helps if you have lots of data in order to feed the deep learning process, for smaller businesses, you may be able to access public data to achieve the same goal, or use pre-existing neural networks to solve your similar problem.

Tools such as Chorus.ai are ready to take your organisation’s live data, in order to provide you with valuable insights in a specific operational area (8). In the case of Chorus.ai it analyses your meetings, particularly sales meetings, to help you get the best performance out of future meetings.

AI is being used to great effect by large corporations such as Walmart to quickly respond when high turnover products look like running out of stock, recently reporting a year-on-year 63% increase in sales (10).

Smaller organisations are also using AI to gain actionable insights, including a Zoo which now has a much better accuracy in predicting high attendance, and therefore staffing requirements, based on using AI to determine all the factors (not just weather) that increase visitor rates (10).

Domo is a tool created to help businesses, small and large, collate data from a wide range of sources (social media, ecommerce, chat bots etc), and help an organisation spot trends in real time (11).
In the area of product design and engineering, a concept called Generative Design underpinned by AI, is enabling faster design and many more possible designs to choose from by allowing all the constraints of the product to be entered, and then allowing the program to generate a large number of possible solutions (13).

However, for a problem more specific to your industry or expertise, you may need to perform a highly customised deep learning experiment. Once you have determined the question you need to answer for your specific area of expertise and industry, there are 7 steps in performing your own AI or deep learning experiment:

  • Gathering data
  • Preparing the data
  • Choosing an AI model to suit your question / domain
  • Training the model with data which contains the results / answers
  • Evaluation of the performance of the model
  • Tuning of the factors determined by the model
  • Applying the model to fresh data in order to gain insights or greater performance. (1)

As a business owner or leader you should be considering the way in which artificial intelligence or machine learning can change the way in which you operate and solve your customer’s problems. Don’t hesitate to get in contact if you would like to discuss how AI can be put to work for your organisation.

Read this article to understand more about how machine learning works, and how artificial intelligence is impacting our world.

If you would like to discuss how AI might benefit your organisation, please don’t hesitate to get in touch with Heather Maloney.

References:
(1) https://towardsdatascience.com/the-7-steps-of-machine-learning-2877d7e5548e
(2) https://www.wired.com/2013/06/baidu-virtual-search/
(3) https://clickup.com/blog/alexa-google-assistant-project-management/
(4) https://aidemos.microsoft.com/ & https://experiments.withgoogle.com/ai
(5) http://www.bizdata.com.au/customer-smartdetect?gclid=CjwKCAjwlIvXBRBjEiwATWAQIseaubDdIaMGue_bjuC9BZU3WLErB1Qj9u12XKmkZGZPz-UGO4balhoCaxgQAvD_BwE
(6) https://www.techemergence.com/machine-learning-fraud-detection-modern-applications-risks/
(7) https://www.techemergence.com/network-intrusion-detection-using-machine-learning/
(8) https://www.chorus.ai/product/
(9) https://www.morganmckinley.com.au/article/how-ai-helping-small-business-today
(10) https://www.clickz.com/5-businesses-using-ai-to-predict-the-future-and-profit/112336/
(11) https://www.techemergence.com/ai-in-business-intelligence-applications/
(12) https://www.engineersrule.com/solidworks-puts-artificial-intelligence-work/
(13) https://www.autodesk.com/solutions/generative-design

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How the pursuit of Artificial Intelligence is changing our world.

April 25th, 2018 by Heather Maloney

The goal of achieving artificial intelligence – a computer that can learn and respond like a human – began in the 1950s(1). However it is only in the last few years that we have seen great leaps forward towards this goal. The reason for the sudden improvements is attributed to break through in an area of technology called neural networks – programming that attempts to mimic the way the brain works, and a feature of the area of machine learning.

Up until the use of neural networks and machine learning, the act of programming a computer to perform a particular task – think displaying words on a screen, adding up columns of numbers, changing an image from colour to black and white – has required that a programmer can describe in exact detail the process of achieving that task. The human brain performs many tasks, seemingly effortlessly, that are virtually impossible for anyone to describe how they are done, beyond some vague concepts and pointers in the right direction. That’s not sufficient to be able to program a machine to do the task. Consider the task of identifying one human face from another – can you describe how your loved one looks, sufficient that another person who has never met them could pick them out in a crowd with any certainty? Very difficult! This is just one example of how amazing the human brain is when it comes to rapidly processing large amounts of information. We perform many such complex tasks almost simultaneously, without even realising.

A neural network is a programmatic attempt to replicate the manner in which it is believed the brain performs complex tasks. The diagram below is a typical representation of a neural network used to carry out a particular task. As an example, consider an input being an image of a face of a person who just passed the camera, and the task to be performed by the neural network being determining whether the image is “Joe Citizen”. The first round of analysis processes the input (camera image of a face) and then passes information about that image in the form of weightings down to the next level of processing. The second level receives that analysis, performs further analysis, and then passes another set of weightings down to the next level, and so on until the end result, which is the most likely answer to the question posed at the outset (where the attributes of Joe Citizen is already known by the program)? The “hidden layers” may comprise many different layers to allow deeper and deeper analysis and greater refinement aimed towards arriving at the correct answer.

Neural network diagram

Machine learning involves allowing a computer program to learn by working through a large amount of data, which also contains the answer to a particular question e.g. data on the observations of humans who both did and did not contract a particular disease in the future. The machine learning program will build a neural network of weightings required to answer the question being posed. Then that neural network is put to work against fresh data to further refine the learning, including humans providing feedback on the program’s accuracy. Finally, armed with all that learning stored in a neural network, the program can then be applied to new, live data in order to interpret that data … it turns out, with great speed and accuracy, surpassing that of humans (1).

The above is a very simplistic description of the way neural networks operate; computer scientists involved in the use of neural networks are constantly improving their performance. Neural networks are still in relatively early days of development, and already there are many different neural network models to choose from, some better at particular problem types compared to others.

An important distinguisher in neural networks compared to “regular” programming is that the neural network can be relatively easily tuned to perform better over time, as well as “learning” from more and more data. A “regular” computer program needs to be manually reprogrammed as requirements change, again requiring someone to describe exactly what is required, and understand all the implications of that change throughout the system.

Machine learning has been applied in the last few years, with great affect, in the following areas:

  • Image / Facial recognition – ever thought about how the image search feature of Google Images, or the speedy face tag suggestions by Facebook upon upload of a photo, have become so good? A person wanted for an alleged crime in China was picked up by security cameras in about 10 minutes of the wanted person entering a concert earlier this month (3).

    City Deep Learning
  • Navigation & self-driving cars – being able to respond to incoming information, such as what other road users are doing around you, is essential for solving the problem of self-driving cars. The amount of technology involved in an autonomous car is awesome – and it needs to be given the life and death involved. “Even if it will take some time for fully autonomous vehicles to hit the market, AI is already transforming the inside of a car.” It is predicted that AI will first bring to our cars a host of so called “guardian-angel” type features to reduce the likelihood of accidents (11).
  • Speech recognition – in the last few years speech recognition (at least for native English speakers) has become very accurate, requiring very little training for a particular person. I now control my mobile phone using voice on a regular basis, because talking to my phone is much faster than typing – apparently 3 times faster according to a study by Standford University (4). Google’s latest speech-to-text system, called Tacotron 2, will add inflection to words based on punctuation to further improve understanding (5) and making it even more human-like when it is reading text to you, or responding with an answer to a question. Speech recognition in devices such as Google Home and Amazon Alexa are making simple tasks much easier. The article entitled “Amazon Echo has transformed the way I live in my apartment – here are my 19 favourite features” shows how speech recognition is being used for hands-free computer assistance in a simple home context (9). Applications of this technology are vast and life-changing for those who don’t have free hands (e.g. a surgeon at work) or are not able to type.
  • Prediction – more quickly and accurately diagnosing a current situation or predicting that a current set of information is an indicator of a future state e.g. in diagnosing disease, predicting financial market movements, identifying criminal behaviour such as insurance or banking fraud (13). The ability of a neural network to process vast amounts of data quickly, and build its own conclusions with regard to the impact of one factor on another (learn) is already helping doctors to more accurately diagnose conditions such as heart disease (12). Reducing the acceptable level of inaccuracy in medical diagnosis will lead to much better patient outcomes and reduce the cost of healthcare to our ageing population.
  • Playing games – a lot of AI research uses games to work out how to train a computer to learn. (8) From time to time I play an online version of the Settlers of Catan board game; when players leave the game (ostensibly because they have lost internet connection … usually it’s when they are losing!), you get the option to continue to game and have AI finish it on their behalf. It amuses me that I find myself, and others, immediately ganging up on the AI player. I mean, they won’t care if you make their game difficult – they’re a robot after all! It was actually the success of a computer to beat the best human players of the hardest game we play that heralded the success of artificial intelligence, and made the world take notice of its capabilities (14). “In the course of winning, [the robot] somehow taught the world completely new knowledge about perhaps the most studied and contemplated game in history.”

But, will the rise of artificial intelligence take away our jobs? Some say yes, others say no (6), but they all say that the new jobs created due to artificial intelligence will be different to current roles, and require different skills (7).

Worse than job loss, will AI cause a computer vs human war or lead to our extinction? Elon Musk is well known for his warnings against AI. It could be viewed that the pressure he has applied to the technology industry helped to lead to an agreement that the technology giants will only use AI for good (10).

I don’t believe that AI will ever result in a computer takeover of the world, because there is more that makes humans different from other animals … not just our ability to think. Reproducing just our ability to think, learn and make decisions, even in a super-human way, does not make a computer human. The capacity for machine learning / deep learning to significantly improve our lives, particularly in the areas of health and solving some of our most challenging problems, is exciting. However, I believe that it is right to be cautious; to move ahead with the knowledge that machine learning could also be used for harmful purposes. Computers can also “learn” the negative elements of humanity (15).

Business owners, innovators and leaders should consider how machine learning might be harnessed for your organisation in order to provide better value, predict more accurately, respond more quickly, or make break-throughs in knowledge in your problem domain. Let’s harness artificial intelligence for good! Read more about “How Business (big and small) can Harness Artificial Intelligence“.

References:
(1) https://www.forbes.com/sites/bernardmarr/2016/12/08/what-is-the-difference-between-deep-learning-machine-learning-and-ai/#4cc961d726cf
(2) https://hbr.org/cover-story/2017/07/the-business-of-artificial-intelligence
(3) http://www.abc.net.au/news/2018-04-17/chinese-man-caught-by-facial-recognition-arrested-at-concert/9668608
(4) http://hci.stanford.edu/research/speech/index.html
(5) https://qz.com/1165775/googles-voice-generating-ai-is-now-indistinguishable-from-humans/
(6) http://www.abc.net.au/news/2017-08-09/artificial-intelligence-automation-jobs-of-the-future/8786962
(7) http://www.digitalistmag.com/iot/2017/11/29/artificial-intelligence-future-of-jobs-05585290
(8) https://www.businessinsider.com.au/qbert-artificial-intelligence-machine-learning-2018-2
(9) https://www.businessinsider.com.au/amazon-echo-features-tips-tricks-2018-2
(10) https://www.vanityfair.com/news/2017/03/elon-musk-billion-dollar-crusade-to-stop-ai-space-x
(11) http://knowledge.wharton.upenn.edu/article/ai-tipping-scales-development-self-driving-cars/
(12) https://www.telegraph.co.uk/news/2018/01/03/artificial-intelligence-diagnose-heart-disease/
(13) http://bigdata-madesimple.com/artificial-intelligence-influencing-financial-markets/
(14) https://deepmind.com/research/alphago/
(15) https://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist

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While you are waiting for a human, try me!

February 13th, 2018 by Heather Maloney

In the last year or so, due to the increased use of online chat, including Facebook Messenger and Slack, chatbots have become much more common. Chatbots are computer programs which interact with a customer in response to information he/she types into a chat tool / instant message program. The increased use of chatbots has lead to maturing of the tools to create chatbots, providing an opportunity for your business to utilise bots not just to provide faster help for customers with problems, but also to support sales enquiries.
chatbotblog

Why would a customer be willing to interact with a bot?

The prime benefit for a customer is to get their problem solved or question answered more quickly. No matter how many people are added to a customer service team, there will always be times of peak enquiry where you have to wait to talk to a human.

Why wouldn’t a customer want to use a bot?

The most likely reason people would rather talk to a human is because they feel that it is harder to get their problem across to the computer, and because of that, it’s a more frustrating process and less likely to result in a satisfactory answer compared to talking to a person, whether by chat or by voice.

What to do?

To overcome the hesitation of people to use chat bots, several strategies have been used in the past including:

  1. Forcing users to first use the bot – Making the first interaction/s or all interactions in your online chat tool orchestrated by the bot, and not accessible by a human, with the option after a period of time attempting to solve the problem, pointing the customer to way to get to other support options. A similar strategy was used in the past with knowledge base functionality, whereby a person submitting a support request via a form was directed to first search the knowledge base, and only then after searching, were they given the option to submit a question.
  2. Pretending to be human – giving the bot human qualities, like attempting personality and humour, and giving them a human-like avatar or photo.

Neither of these strategies are very successful. People know when they are talking to a person, so trying to pretend otherwise can be felt as offensive to the intellect. Forcing people to use a bot first, again adds to the frustration of getting a result.

I believe that both chat and bots have their place in the provision of customer service. If I can get further information about a product I am considering via online chat, I am more likely to buy. It’s great knowing that I can just jump onto a chat within a website or web application, ask a question, and get an answer without having to dial up, sit in a telephone queue, and finally get through to a person. If on the way to getting my chat question answered, a bot steps in to try and help me get my solution more quickly, then I’m fine with that too, as long as I can differentiate the two types of assistance, and I can choose to ignore the advice of the bot and still get to chat to a real person, even if that takes longer.

Chatbots are great to help organisations provide 24/7 support, attempting to answer the question when an operator isn’t available, but allowing a person to take over the enquiry when the next support shift starts.

Steps to Creating a Useful Bot

When a human provides customer service the first step is to understand the enquirer’s problem. If they have heard the problem before, a proficient customer service operator can very quickly rectify the problem or provide the right guidance to the customer. Understanding the problem, of course, relies on the customer describing the problem in a way that’s understandable by the customer service person. And therein lies the difficulty. People describe the same problem in a myriad ways because they don’t always understand the nature of the problem themselves.

Take someone who has forgotten their password as an example. Whilst you may think most people would understand how to describe that in the fewest number of words, those who are less technically savvy might not realise that’s their problem. They may instead report that as “I can no longer login to your system”. In such a situation, a human being knows to quickly ask questions based on the statements made by the customer, and will glean clues from their tone and manner and the way they say those words. The customer service person could ask “okay, did you type in your username and password?” or they might say “when was the last time you logged in?” The answers provided by the customer will allow the support person to discover the root cause of the caller’s issue. If a bot is to determine the cause of a customer’s problem and the best solution, it needs to be able to interact with the customer and know the right questions to ask based on the way that a person communicates the problem. This is the challenge of programming a bot.

Step 1: Choose the Most Common Problems

Because it is challenging to program around the issues that people have, the first step when creating a new bot is to choose the most common problems or most frequently asked questions, that your customer service team currently deal with. Issues such as forgetting your password are unlikely to be the most common problems reported to your team, as such issues are likely already made easy for the customer to solve on their own. However, there will be issues that occur over and over, or questions raised on a regular basis, that you will be able to identify and solve, even if that is by pointing the customer to the right help article. Look for common categories of problems, as well specific issues and questions that re-occur.

Step 2: Document how people describe the problem

In order to program a bot to assist customers with a particular problem, you need to identify all the common ways that a person may describe the same problem. That’s when they actually know what the problem is. For example for those who realise that they have forgotten their password, there are still many different ways that a person may say that. They may say “I don’t know my password”. Or “I have forgotten my password”. Or “I have forgotten my login details”. Or “I don’t know what my password is”. Or “I need a new password”. Or “I have lost my password”. Or “Please reset my password”. These may not sound that different to a human, but to a simple computer program, they have similarities but they are all different.

You are likely to find that the one statement by a customer could actually require different solutions depending on their answers to other questions. Back to our password problem, if a user says “I can’t login” then the next question might be “Have you forgotten your password?” if the answer is no, then the next question might be “Have you forgotten your username?” and may lead to yet further questions. If the answer is yes, then the answer may have reached the end of the logical decision tree, ready for the solution.

As you document the questions that may be asked in order to discover the actual problem, you are likely to identify other questions and problems that you can solve along the way. You will need to decide how much time you will spend on these other problems based on how common they are, but at the same time, you don’t want to leave the customer hanging.

Step 3: Determine how the bot will direct the customer in order to solve the problem, or answer the question

Once you’ve worked out all the different ways a support request could be phrased by a customer and the questions you need to ask to get to the root of the problem, then you need to work out how the bot should respond. In the case of a password reset being required you may then program the bot to provide the password reset link. A password reset is a very simple problem to solve. The most common problem for you maybe something much more complicated.

The solution could be one or more of: providing a link to a help article which explains how to carry out a task, suggesting a list of possible products that meet the customer’s requirements, providing a link to a step by step screen overlay guiding the user through solving a particular problem, or staying in the chat in order to wait for a human to help.

Step 4: Test

Having programmed your bot to handle some common problems, it is now really important to test it with customers. You will gather much information about how useful it is by looking at your customer’s interaction with it.

If you give your customers the ability to rate the support they received or the help article you delivered to them, they actually may not choose to rate you, but you should still be able to see if they then needed to ask another question, or the same question in a different way.

Step 5: Refine and Extend

You should expect to continue to build on the list of questions or ways that a customer can ask about a particular problem. Over time you will also find the problems that are coming out the other end and not solved by the bot become your new most common problems. As I mentioned not all customers will be comfortable chatting, or chatting with a bot, so multiple support options should be provided.

Where can I place my bot?

Chatbots can be added into your mobile app, web application or website, but also into your Facebook page, Slack and other chat tools that are being used by your business. Where you will place your bot will help you select the tools you use to build it.

If you need help working through the process of creating a bot for your organisation, we would be very pleased to help.

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Online Chat Game Changer for Customer Service

February 12th, 2018 by Heather Maloney

Live chat has been around for many years, and is well documented as providing quicker and more convenient customer service, leading to happier customers, and website visitors more likely to make a first time and repeat purchase. With the more recent proliferation of Facebook Messenger and Slack and other chat tools for internal communication and collaboration, customers are more and more looking for chat options to solve their problems and get answers quickly.
Call center worker accompanied by her team.

We have been using an online chat tool within Enudge for a year now, and have also found it to provide greater opportunity for us to interact in a timely way with prospects, and has improved our client’s satisfaction.

There are two distinct ways that chat can be used to provide customer service:

  1. Real people ready to chat online to solve a person’s problems.
  2. Bots – computer programs which, at their most sophisticated, respond to natural language questions to provide humans with the answers they seek, without the need for a human

Having real people responding to customer enquiries via online chat can be more efficient and effective than dealing with phone calls in the following ways:

  • customer service personnel can often deal with multiple enquiries at a time, saving on-hold wait time for the customer
  • the customer can submit their question, and leave their screen at the place of their question if they do have to wait, and continue on with other things without having a phone call tieing up their phone line
  • if a customer service operator doesn’t respond in a certain period of time, chat tools can often be configured to request contact details to follow the person up at a later time
  • providing customer support in writing avoids issues of difficulty with spoken accents and poor VoIP lines

Online chat tools also provide a range of other features over call centres:

  • build a knowledge base of responses over time
  • easier access to data, such as common questions, for the full customer support team and management
  • ability to easily hand more difficult questions over to a specialist support person, with full details of the response immediately available
  • bots contained within some chat tools can utilise a knowledge base to provide suggested answers to the customer’s question based on previous answers, thus providing the solution more quickly
  • allow customer service people to more easily work remotely

There are numerous chat solutions available for adding chat to your website, web application, or mobile app. Many of these work across both website and mobile apps, allowing you to easily co-ordinate responses across all channels. The tool you choose will depend on the functionality that you require, and the platform in which it needs to operate. Please don’t hesitate to get in touch if you would like our help to choose and implement chat.

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Online Chat for Collaboration and Team Work

February 9th, 2018 by Ammu Nair

slack-logo-small
Despite threading and advanced searches added to newer versions of email clients, it is becoming increasingly difficult to keep track of email threads that are a mile deep, and segregate discussions based on projects.

The implementation of Slack into Contactpoint has helped us to solve this problem by providing a way to organise conversations into what are called “channels”. You can create ‘open channels’ to post company wide announcements, which are available to all members of the company. More confidential or private messages that needs to be exchanged between team members of a particular project can be carried out in ‘private channels’ – this means Slack allows us to create channels for different projects, topics or conversations between certain team members of our organisation. Direct messages offered by Slack, are just quicker, shorter and better alternatives to email messages. We can get a quick message to each other without having to write on sticky notes, or craft a properly structured email.

Slack has also made it quite simple to search for that link to a great resource that someone in your team posted 3 weeks ago! Slack searches can be filtered – which allows you to search only in specific channels, or only in messages from a particular team member – and can be sorted.

File-sharing, one of the basic prerequisites of collaboration, is supported by Slack which allows you to share all kinds of files in a hassle free manner by drag-and-drop or from Google drive or DropBox. The shared files can also be searched through, or starred as a favourite for later / quicker reference. Paste the link for your Google Drive spreadsheets or DropBox file along with comments, and these files will be in sync and searchable instantly. That brings me to another great feature that makes Slack a one-stop platform for collaboration. Slack can be easily integrated with a large number of apps in the market – yet another way to have all your information in sync, as it allows centralised access to all your notifications. This has greatly reduced our effort and time in switching between different tools and apps, while checking notifications. Apart from Slack’s huge collection of pre-built integrations, Slack has known to be very flexible in allowing you to build your own integrations quite easily, thereby making it advantageous for large organisations as well. Imagine your IT team receiving notifications when a new Zendesk item is created, or your team receiving a notification when when your daily web traffic exceeds a certain number of visitors. Pretty cool, isn’t it?

Integration is what catapults Slack into a category all its own. The solution enables you to centralize all your notifications, from sales to tech support, social media and more, into one searchable place where your team can discuss and take action as required. We have built our own integration with Slack so that online chat enquiries from Enudge are immediately pushed to a particular Slack channel, helping the appropriate customer service staff to see the enquiries without delay, and then see the solutions in the same place.

Slack also provides you a companion – Slackbot – to remind you of a meeting, or even remind your colleague about lunch time! Whether you have a team member working remotely, or you are working alone, Slack serves as an excellent tool to increase your productivity, by allowing you to schedule reminders, meetings, or even setup video and screen-sharing calls.

With apps for Android, iOS and Windows, all the Contactpoint team are now well-connected, and our messages are with us, no matter where we are!

Slack, is being employed for similar reasons across many large corporations as well as small businesses. For example, Oracle recently introduced Slack organisation-wide. Other tools are available, and in fact we have used other online chat tools for many years prior to implementing Slack. However, with the ease of integration across platforms, and the many add-ons which can be easily installed, Slack has quickly provided many improvements for our organisation and ways of working.

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Controlling my App using Voice

October 15th, 2017 by Heather Maloney

Adding voice recognition to my mobile app
In order for the apps on your smartphone to be voice controlled, they need to be specifically programmed that way.

Some of the more common voice-enabled apps you are likely to find on your smartphone are:

  • Calendar – ask your smartphone the time of your next / first appointment, on a particular day, and it will tell you the answer and automatically show your calendar appointments for that day on screen
  • Phone – tell your smartphone to call person X, or send a text message to person Y, and it will take care of these tasks, prompting you for the details as required
  • Alarm – set an alarm to go off at a particular date and time
  • Search – ask your phone to search for a topic, and it will display a clickable list of search results

Voice recognition technologies have improved significantly over the last few years, providing numerous options with regard to voice enabling mobile apps, including:

  1. The Android operating system for wearables (e.g. Galaxy watch), smart phones and tablets includes in-built voice control actions for carrying out commonly used tasks such as writing a note. It also comprises the ability for an app to include its own “intents” which listen for voice activation once the user has launched the app. Finally it includes methods for allowing the user to enter free form text for processing by your app.
  2. Google Voice Interactions API – a code library provided by Google which allows an app to be triggered via the Google Now interface – that’s what you’re using when you say ‘Okay Google’ and then say a command.
    okay-google
  3. Apple devices (iPhones, iPads, iWatch) are built on the iOS operating system. Native iOS apps are written in either Objective C or Swift (a more recent language). With the launch of iOS 10, the Swift programming language included a Speech framework to allow developers to more easily implement listen for voice commands, and manipulate voice into text for use within apps.
  4. SiriKit was released in 2016, providing a toolkit for iOS developers to add voice interaction through Siri into their iOS 10 apps.

    What-is-my-heart-rate-voice-interaction-with-mobile-app
  5. Cross platform apps need to use 3rd party libraries to interface with the native speech recognition functions.

It’s important to know that the speech of the user is processed by Apple’s servers or Google’s servers, and then returned to the mobile device, so some lag may be noticed particularly when dealing with longer bursts of voice. It may also have privacy considerations for your users.

3rd party APIs exist which are completely contained within the mobile device, meaning that the user doesn’t need to have an internet connection to use them, and the privacy issues are reduced. An example of such a 3rd party API is the CMU Sphinx – Speech Recognition Toolkit. The downside of using such a library is that you can’t avail yourself of the amazingly accurate voice recognition the large players have developed over time, including for many different languages.

Obvious apps which provide the user with significant benefit from the use of voice control include:

  • An app which improves or assists the job of a hands-on task e.g. chefs, surgeons, artists, hairdressers …
  • An app which is needed while a person is driving e.g. navigation, finding locations, dictating ideas on-the-go …
  • An app needed by a person with disability.
  • An app which involves the entry of lots of text.

We expect to see more and more support for voice in all sorts of applications in future. What would you like to be able to achieve through voice commands?

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