Tag Archives: machine learning

Voice-Activated Shopping an Effortless Customer Experience

Is voice-activated shopping the digital outcome that retailers need to offer their customers an effortless shopping experience? Or is it taking AI and machine learning a step too far?

Humans are what we are because of our ability to speak with one another, to listen what’s said, to comprehend the info and to react on what we perceive. We also like to be part of a group, to socialize. Said MacFarlane 2, (2014): “Because our evolutionary heritage provides us with genetic material open to forces and influences from the physical environment, we also require a social environment for brain development and for the acquisition of skills such as speech and written communication.”

So we learn from others and learn others by using our voices. But that is now changing. Now, after millions of years of being humans, we’re learning machines how to listen to voices, to recognize and analyze the message and then to respond in a ‘sensible’ way.

So, if you’re still able to speak, say Hallo! to voice-activated shopping. Because, according to Hailee Sosnowski’s post in DigitalCommerce, voice search is projected to account for half of online searches by 2020.

What is Voice-Activated Shopping?

Voice-activated shopping (VAS) means that a customer can use his or her natural voice to control technology whilst shopping. There is no need to touch anything and the customers can do voice-activated shopping by using their smartphones. VAS is already adopted by some retailers.

Laura Agadoni (JLL) remarked the following about voice-activated shopping: “Right now it’s being used for ordering groceries, pizza or coffee. For consumers there’s no driving to stores, logging onto a computer, or pulling out smartphones to open an app. They simply say what they want to one of the new voice activated devices coming onto the market from the likes of Google and Amazon.”

Take the example of Alexa, the AI-based personal assistant from Amazon. With Alexa in your kitchen, adding an item to your Ocado order is a breeze, says Holly Godwin (OcadoTechnology). Run out of biscuits and have a friend coming for tea? – Just tell Alexa “Alexa, ask Ocado to add biscuits”.

Alexa converts the audio stream into a command (for example, “add to trolley”) and a search term (such as “biscuits”). Alexa most probably will find exactly what you want, because Ocado has ‘trained’ Alexa to recognize the top 15,000 commonly search terms from Ocado.com.

How will Voice-Activated Shopping affect the retail market?

In today’s age of digital driven technology, it’s no shame to ask how voice-activated shopping may further disrupt the retail market. However, there is no consensus about what the opportunities or challenges of VAS are for retailers.

Opportunities using VAS (OnlyRetail.com)

  • More sales. Amazon found that sales of its Echo devices increased nine fold compared to 2015. Also, they also spend 10% more and their buying frequency went up by 6%.
  • Shopping for customers is now effortless. VAS allows householders to buy groceries just by talking to the fridge.
  • Gathering data for an omnichannel approach. Voice-enablement could be the unifying force omnichannel has been missing.
  • Investing for the future. It’s been reported that 55% of 13- to 18-year-olds use voice search every day, so clearly there is an appetite (Emma Lyons, Campaign US).
  • Speed of ordering. The ability to immediately order household essentials is the most obvious use for voice-enabled retail.

Challenges using VAS

  • “It’s still quite a new market and quite complex, so it requires advice and people will want to come talk to someone who can explain how it works, so we see it as an opportunity in that respect,” according to Grace Bowen, RetailWeek.com.
  • Tailoring search algorithms for Voice-enablement. “We know that shoppers will not go past the second or third page of a Google search result – voice will be like that on steroids” (Luke Tugby Retail Week).
  • Acceptance of VAS. Older generations may take a bit more convincing to adopt voice-activated technology.
  • Universal use of VAS in retail. A big question is whether voice recognition technology can work for all retail. What about fashion? Consumers can’t very well order a “black dress,” for example, and get exactly what they want, wonders Laura Agadoni (JJL).

Concluding

Speech has been argued to be the most natural and comfortable way to communicate 1. So it came as no surprise that it is now integrated in AI technology. So, what do commentators say about voice-activated shopping technology?

“Voice recognition technology is the next iteration of online shopping as consumers increasingly prize ways to complete chores or get the information they need easily and quickly,” Laura Agadoni (JJL).

“The convenience of voice search makes it instantly attractive to consumers, but it also introduces new complexities that retailers who want to survive the age of voice must fully understand,” Hailee Sosnowski, paid search planner, BKV (DigitalCommerce360.com).

My advice? Are your business performing as planned? If not, revisit your business’s digital marketing plan and identify the problem areas. If the most important reason why your business is losing sales is that your customers seeks VAS, then do VAS!

Read also: Artificial Intelligence – Digital Outcomes or Digital Disruptions for Retailers?

Notes:

1 Kääriä, A.  2017. Technology acceptance of voice assistants: anthropomorphism as factor, Master’s Thesis, University of Jyväskylä.

2 MacFarlane, A.E. 2014. Voice activated: exploring the effects of voices on behaviours., PhD Thesis, University of Canterbury.

Image:

Flickr.com

Marketing Automation is enabled by Artificial Intelligence, Big Data and Chatbots

“Marketing automation is growing – sizzling fast, announced Michael Jans recently in his blog AgencyRevolution.com. In fact, there are eleven times more B-B companies using marketing automation than were in 2011 (VBInsight). Most visible marketing automation for retail customers are chatbots.

Advancements in artificial intelligence (AI), coupled with the proliferation of messaging apps, are fuelling the development of chatbots.  Artificially intelligent chatbots or conversational agents can be used to automate the interaction between a company and customer.

What is Marketing Automation?

Marketing automation, in general, complements interactive and direct marketing with the help of automation and further on in CRM and email marketing 4. The goal of marketing automation is to target the right customer with the right content 1. To achieve this goal, the optimization of customer data – e.g. name, contact information, transactional data is critical. Consequently customers can be targeted with the right message. Therefore marketing automation allows marketers to respond instantly to identified opportunities in real-time even outside the marketing plan.

This use of marketing intelligence provides valuable management insights to markets, customers and campaigns and leads to enhanced efficiency. Also, this same use of data enables customers to receive personalized, relevant messages and offers at appropriate times. As result of this, customer experience is improved significantly. Indeed, Sarah Burke of Spokal concurs: “Marketing automation is a super effective tool when it’s used to supplement our marketing efforts in an attempt to make the lives of our customers even better”.

However, marketing automation is facilitated by Artificial Intelligence.

Artificial Intelligence

Techopedia defines Artificial intelligence (AI) as an area of computer science that emphasizes the creation of intelligent machines that work and reacts like humans. AI is becoming part of our lives ever more. Today we can ask a computer questions, sit back while semi-autonomous cars negotiate traffic, and use smartphones to translate speech or printed text across most languages. For AI to work properly, the machines or robots needed to be ‘learned’.

Machine learning is the process that offers the data necessary for a machine to learn and adapt when exposed to new data. Nello Cristianini suggests we should think of it as training a machine: “It depends on the other two methods by reading mined data, creating a new algorithm through AI, and then updating current algorithms accordingly to “learn” a new task.”

For most retailers and marketers in the digital economy, the intelligent ‘machines’ of choice are chatbots. However, chatbots are dependent on a host of interconnected and emerging technologies, many of which rely on machine learning and require massive amounts of data 3.

The use of data to enable Marketing Automation

Douw G Steyn, owner of the Bricks2Clicks (this blog) had this to say about Big Data: “One of the fall outs of the digitization of business is the massive amount of data that are everywhere. Every time a customer makes a purchase online or registers online, data is generated. The data can potentially tell you almost everything about consumers.”

Randy Bean in MITSloan commented on the use of Big Data with AI: “The impact of Big Data goes well beyond simple data and analytics. Big Data and AI in combination are providing a powerful foundation for a rapidly descending wave of heightened innovation and business disruption. While the first wave of Big Data was about speed and flexibility, it appears that the next wave of big data will be all about leveraging the power of AI and machine learning to deliver business value at scale.“

Data mining can find the answers to questions that you hadn’t thought to ask yet. What are the patterns? Which statistics are the most surprising? What is the correlation between A and B? (upfrontanalytics.com).

“Intelligent machines need to collect data – often personal data – in order to work. This simple fact potentially turns them into surveillance devices: they know our location, our browsing history and our social networks. Can we decide who has access, what use can be made of the data, or whether the data gets deleted for ever? If the answer is no, then we don’t have control” says Nello Cristianini in the New Scientist.

Chatbots as interactive conversational platforms

By definition, a chatbot is a computer program that responds to natural language text and/or to voice inputs in a human like manner 2. Chatbots can run on local computers and phones, though most of the time they are accessed through the internet (Chatbots.org). Moreover, the effectiveness of Chatbots is depended on the quality of the source data and how well they are programmed. They are after all robots! And robots need to be learned…

Once a customer starts to interact with a chatbot, the chatbot’s software identifies the customer. The chatbot will then have the demographic information of the customer, her purchasing history – such as what products she’d purchased most frequently, what time of the year she does most of her shopping, and when last did she purchased? The scope and depth of information can be never-ending.

The  of a typical conversation between a chatbot and a retail client (image: Chatbotsnewsdaily)

Eric Samson writing in Entrepreneur.com mentioned 7 benefits using chatbots as marketing tools

  1. Customer service – by providing the chatbot option for customers, you will lower the stress of dealing with customer service and increase customer satisfaction with your brand.
  2. Consumer analysis – chatbots can play a large role analysing customer data, and optimizing sales and marketing strategies in light of this analysis.
  3. Personalized ads – another chatbot strategy that’s proven to be successful is the creation of personalized ads.
  4. Proactive customer interaction – chatbots are ideal for “reach out” initiatives. To do this, the accompanying action should be something small, like inquiring whether or not the customer needs assistance.
  5. Site feedback – chatbots are great for reaching out to customers via simple questions and the gathering of feedback. This strategy is useful, especially for website optimization.
  6. Lead-nurturing – using the information that chatbots collect about a customer, you can create customized messaging that guides the consumer along his or her “buyer’s journey,” ensuring movement in the right direction that achieves higher conversion rates.
  7. Maintain a presence on a messenger act via a chatbot – by maintaining a presence on a messenger app via a chatbot, you can save money while simultaneously remaining available for your customers 24 hours a day.

According to Chatbot Conference, the 3 main disadvantages of chatbots are:

  1. Too many functions – most of developers strive to create a universal chatbot that will become a fully-fledged assistant to user. But in practice functional bots turn out not to cope with the majority of queries.
  2. Primitive algorithms – AI chatbots are now considered the best as they can respond depending on the situation and context. However, complex algorithms is required for this purpose. Meanwhile, only IT giants and few developers possess such powerful technological base.
  3. Complex interface – talking to a bot implies talking in a chat, meaning that a user will have to write a lot. And in case a bot cannot understand the user’s request, he will have to write even more. It takes time to find out which commands a bot can respond to correctly, and which questions are better to avoid. Thus, talking to a chatbot does not save time in the majority of cases.

Concluding

With Big Data, Artificial Intelligence and Chatbots there aren’t a clear ‘pecking order’. The Upfront Analytics Team explain it as such: “Data mining, artificial intelligence, and machine learning are so intertwined that it’s difficult to establish a ranking or hierarchy between the three. Instead, they’re involved in symbiotic relationships by which a combination of methods can be used to produce more accurate results.”

The speed at which technology is moving forward – “software is developing software” and “machines are building machines” an affordable, practical usable chatbot for customer care and marketing is not far away…

Read also:

  1. Predictive Analytics helps Retailers to make sense of Big Data
  2. Chatbots in Retailing – a Fact or a Fad?

Notes

1 Mattila, J. 2016. Customer experience management in digital channels with marketing automation, Master Thesis, University of Oulu, Department of Information Processing Science.

2 D’Haro, L.F. and Lue, L. 2016. An Online Platform for Crowd-sourcing Data from Interactions with Chatbots. Proceedings of WOCHAT, IVA.

3 Etlinger, S. 2017. The conversational business: How chatbots will reshape digital experiences, Altimeter.

4 Sandell, N. 2016. Marketing automation supporting sales, Master’s Thesis, University of Jyväskylä.

Image

Pixabay