ECommerce is Dead. Long Live iCommerce!

Over the past two decades or so eCommerce has undergone a major change.
The speed of this change has been, and continues to be, amazing.

A Short History

The world wide web got invented in 1989, became available on the Internet
in 1991; first web sites humbly started as additional marketing channels,
with corporate web sites giving information on the company and a product
catalogue; 1994 the Netscape browser arrived. In 1995 Amazon got founded –
and the story started to take off. In 2000 we saw US online shopping
eclipsing the 25 billion dollar mark. 2003 we saw iTunes and in early 2005
there was already talk about ‘fully personalized shopping experience’. Read this!

Not to forget that Google got founded in 1998 and Facebook in 2004 – and
with them data collection and its –use for advertising started to happen en
masse.

In 2007 the iPhone arrived, followed by the iPad in 2010 – and a whole lot
of additional demands got created. mCommerce arrived. Device friendly
sites and eCommerce presences became mandatory.

Multi Channel needed (and still needs to) become omni-channel.
About 2012 Big Data became mainstream although the term has been around for
longer.

2016 then became the
year of AI, conversational commerce, and bots. And these technologies may very well be the saving grace for eCommerce.
Will they?

The Customer Side

In parallel, partly caused by what is possible and partly simply because of
rising demands, customers developed an ‘I want it right now – and right
here’ expectation; this is combined with a
fading trust into institutions
that to some extent got fuelled by too much scatter-gun advertisements. Add
the meteoric rise of social media. This led to the (wrong) notion that the
‘customer is in control’ and to the need of analyzing lots – LOTS – of data
and to rapidly deliver customers contextually relevant information – at the
right time and into right channel.

Today, customers expect their experience to be flawless; they expect that
relevant information be easily found, that recommendations coming from
businesses are geared to their needs and that no irrelevant ‘clutter’ is
displayed to them.

Of course they expect that help be in easy reach at any time, if they need
it.

Where does AI come into the Picture?

Of course, the first thing that comes into mind is the provision of
intelligent product recommendations. There are the Amazon’s and Netflix’s
of this world who have built whole business models around delivering the
right recommendation at the right time – and do this very well. And there
are a number of solutions out in the market that do exactly this for
eCommerce sites.

An important aspect is to combine this ability with other channels, in
order to not only incentivize the cross- and upsell, but also repeat
business. Intelligent product recommendations are a powerful tool to invite
customers to become return customers.

AI supported predictive and prescriptive analytics, supported by an
automated delivery of the determined content through the right channel
helps to keep customers engaged and to then drive business. Delivery could
be into the site in real-time to drive cross- and upsells, or at a time and
through the channel that is likely to get the best possible engagement in
an attempt to re-engage for further business or to convince a customer to
re-engage with an abandoned basket.

Similarly, an eCommerce site can offer individualized, or personalized,
pricing, which is a specialized form of dynamic pricing that determines a
price based upon the customer and the company’s objectives. The company
can, e.g. give a one-time price discount for an unknown shopper who seems
to be on the edge of buying, or give just the little incentive to a known
loyal customer as a reward. Knowing the customer this incentive could even
be a free accessory that the company knows they are interested in, instead
of a discount.

In parallel, and based upon a user’s current and past behavior the
eCommerce site could offer a chatbot offering support to find a suitable
product or configuration. This can be in the form of a support service or
be a virtual agent as it is, e.g. offered by
Dominos
in Australia or New Zealand, where a customer can use a conversational
interface, supported by Natural Language Processing to configure and order
pizzas. This can, especially with a larger number of products, greatly
increase the speed of ordering. Add an Alexa/Siri/Cortana-like voice system
and things become really interesting.

Or how about having an AI-based configurator that helps creating a
configurable product? Look at Bear Naked Granola. Using
this site one can build an own flavor of Granola with some help of IBM
Watson. On the B2B side CPQ is another example where AI is applied.
Salesforce added Einstein functionality to their CPQ solution, while Apttus
invested in AI for their CPQ solution. This can result in offering the best
possible solution and quote for a customer.

A bit more on the esoteric side one finds solutions that offer AI-driven
web site optimization, like Wacul,
while research already looks into fully adaptive web sites – sites that
automatically improve their organization and presentation for individual
users by learning from the users access patterns of the site and probably
additional ones.

Simpler solutions just translate the content of a web site. Try Google
translate on the (Japanese) Wacul site. You will be amazed what this AI is
capable of doing.

What Does It Mean?

There are many possibilities to use AI and machine learning to improve an
eCommerce site, the most obvious ones being highly targeted product
recommendations, pro-active decision support and the friction reducing
possibilities that a conversational interface offers.

This in an integrated manner across channels (to avoid the term
omni-channel).
The overarching goal is to make the eCommerce experience as simple and
frictionless as possible for the customer.

So, will AI be the future of eCommerce?

ECommerce does not need a savior and AI will surely contribute to
providing new, more convenient, and exciting experiences for the customer
that lead to better results for the business. Realtime and intelligent
actions and reactions will make the difference in future and turn eCommerce into
iCommerce.

Better be on the right side of it.

Working off an existing eCommerce presence business leaders therefore
should:

• Proactively offer automated help in situations where the customer seems
  to become unsure about how to proceed, using an intelligent agent as
  opposed to pushing a chat window onto the user’s screen
• Have a deeper look at the possibilities that hyper-personalized
  recommendations offer, providing customers with exactly the recommendations
  they would need in support of their intended purchase
• Look into offering a conversational experience for customers that enables
  them to avoid browsing a category tree but give some ideas of their own and
  receive matching suggestions, also considering browsing and purchasing
  history. As in-store, let your customer ask for a ‘silky, blue, light
  summer dress, sized 38’ instead of browsing the catalog, studying the
  product description and then finding out that the size is currently out
• Consider personalized pricing as part of the customer acquisition- and
  loyalty strategies. There can be benefits for both, offering the hesitating
  unknown customer and the well known high value customer.
• Intelligently use their web site logs, having an intelligent agent
  continuously suggest improvements to the site that are geared towards
  further reduction of customer friction

And keep an eye open to offering customers an individually unique brand
experience. The data is there – the automation intelligence (soon), too.