What do the terms multi-channel, cross-channel and omni-channel retailing mean? Let’s examine the different terms used today to describe recent evolutions in the retail space, where performance is now measured across several different channels. And in our next article, we’ll discuss how to monitor performance in a multi-channel context, while also considering the protection of personal data.

“What is understood well is expressed clearly.”*

The term multi-channel describes the experience of a customer who shops using the different channels made available by a company, such as brick-and-mortar stores, catalogues, website, mobile application, TV commercials, and call centres.

Multi-channel is not a new concept. Before the advent of the Internet and mobile, it was possible to purchase via different channels including shops, call centres and mail order catalogues. What is new, however, is the growing number of channels used today, and the multiplying devices used to access them, such as desktop computers, smartphones, tablets, interactive terminals, and smart TV. These channels will continue to increase as we see more “smart” devices develop, like cars and fridges.

The term cross-channel describes the experience of a customer who has used a combination of several different channels for the same purchase. For example, a customer prints a product configuration on a company’s website and then goes in-store to make the purchase. A customer may also choose the product he or she wants to purchase from a company’s catalogue, and then buy the product directly on the company’s website. Another example is a customer who purchases through his or her TV set, and then collects the product from the nearest store.

The term omni-channel describes the simultaneous use of two channels, like using a mobile phone while in-store, or a tablet while watching TV. The term is also used to describe the consistency between different channels that facilitates and streamlines customer interactions.

This means that a customer’s configurations and preferences saved on one channel must be memorised and accounted for on all other channels. As a customer, could you imagine if you had to recreate an account for each different channel used (desktop computer or tablet, or in-store checkout)?

These new terms also support an underlying idea put forth by service providers and championed by digital marketing experts, which can be summed up as follows: Businesses who do not think “multi-channel” are doomed to disappear. But as always, we must exercise caution when making categorical judgments such as this one, especially when there are no figures to rely on. Just because everyone repeats the same thing does not make it an absolute truth.

Dismissing preconceptions about multi-channel

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Your data is there to help you rule out preconceptions, like the ones that follow, surrounding the emergence of multi-channel.

#1 Customers like to use all channels as soon as they are available

If customers use several different channels it is not for the sake of using them, but rather they find them important. Having a wide range of channels available meets one of their needs:

  • saving money: customers using a mobile device in-store can take advantage of the latest promotions, collect their product in-store after online purchase to avoid paying shipping fees
  • reducing risks: customers might go in-store to view a product they discovered online in more detail, or they might reserve a product using their mobile phone for fear that the product may no longer be available in-store
  • reducing efforts: customers may choose their product from a catalogue and insert the product reference number into the mobile application to purchase it
  • saving time: customers might use smart TV to show a product to the whole family and get their approval, then later purchase the product when they’re alone from the store closest to their workplace.
  • obtaining further information: a customer might use his or her mobile phone in-store to consult more detailed technical information or reviews about a product.

#2 All channels must have the same offerings

Businesses fear that customers will not be able to find a product on all the different channels available – and this drives retailers to provide the same offerings on all channels. But there’s a risk in underestimating the particularities of each channel and the customer segments targeted with each (like young people for mobile channels, older customers for catalogues). Slide 22 of a recent study carried out by Mappy-BVA-Novedea Group confirms that a relationship exists between age, socio-professional category and the tendency to buy online or in-store. By striving to provide the exact same offerings on all different channels, business miss the opportunity to make the most of the differences existing between each channel.

#3 A customer who uses several different channels is more likely to make a purchase

We have all read statements such as “Multi-channel provides a higher conversion rate”, “A multi-channel customer generates sales six times greater than a single-channel web customer.” But is it really multi-channel that leads to a higher conversion rate? Yes, of course, making an offer available on several different channels means that brands won’t miss out on selling to people who like using different channels. But more likely, higher multi-channel conversion rates can be explained by the fact that customers who use several different channels to make a purchase have a stronger intention to buy. Trying desperately to move visitors from one channel to another will not necessarily increase your sales turnover. The intention to buy trumps the use of multiple channels. The bottom line is that sales will not take off if your product is poor, no matter how unique the experience you offer through your distribution channels.

All of these statements are only hypotheses. The work of a web analyst is to confirm if the statements are true by using figures, or by disproving them if need be. The web analyst must help their Marketing Manager sort all of the opinions published online. As a result, it is necessary to test and analyse the data. AT Internet, through its Web Analytics and Mobile Analytics solutions, provides data on these two main channels. Your in-store or call centre data can also be integrated via API to supplement this online data.

The only remaining problem is the question of protecting the personal data of prospects and customers, which we’ll examine in our next post. AT Internet is very vigilant on this subject and our Analytics Suite 2 is 100% compatible with the GDPR. We consider all the data we collect to be “personal data” and as such we apply the same level of care and protection.

The first part of this article on cross channel showed us two extremely important points:

  • the issue is more complex than one might think
  • we must beware of reductive and categorical arguments, of which analysts are inherently wary

This naturally leads us to multi-channel tracking, where we’ll see that different companies’ offerings hide some significant constraints.

Managing and analysing “multi-channel” performances: they don’t tell you everything

Building on the assumption that the multi-device experience (desktop, tablet, smartphone, smart TV, etc.) is undeniable, thanks to the multi-channel brand interactions it offers consumers, let’s now take a look at the most frequent tracking and recognition use cases from two complementary angles: relevance and confidentiality.

To correctly monitor user experience (and therefore optimise it), we need to be able to associate a single consumer with a series of items, some of which are exclusive to the consumer in question, some of which are shared. Without this key, all results would be unreliable, as would be any analyses stemming from them. And there are different ways of obtaining this key, some of which raise problems with regards to consumers’ informed consent.

Let’s study a few examples:

When using everyday consumer services online, most of us have been asked to share a phone number, in addition to providing our email address, with the rationale of “protecting” us, the consumers. But behind this display of goodwill, might this actually be a simple but masked way of recognising mobile visitors and linking our web and mobile activity?

“Fingerprinting” is already used in the United States for the purposes of targeted advertising.

In the United States, a class action suit against Google – who allegedly scans Gmail messages for “spam blocking and viruses” – is another more underhanded example. While it’s unlikely that Google will expose the minute details your private life, is it unreasonable to think that this data collection might be used to qualify databases, and be linked with the notorious AdID (unique advertising ID)?

While databases are happily filling up without respecting the principles of the GDPR, let’s have a look at these well-known recognition techniques.

What are the different recognition systems?

#Identified visitor (the simplest case): each user defines their personal identifier, which remains the same regardless of the channel used (this is usually done when creating a user account on the site). Here the consumer has voluntarily provided their identity and agreed to be recognized. This will be used as long as they connect to their account, regardless of the channel, and the analyst will be able to analyse their complete experience with the brand.

  • Relevance: accuracy and completeness guaranteed.
  • Privacy: no problem as long as the consumer has been clearly informed of the use of the data at the time of creating their account.

#Cookies (text or flash) recognition system:

A cookie is a file that is added to the browser and stores usage data. It requires the explicit consent of the consumer to be implemented. A cookie set will remain on the browser concerned for a period of 13 months. If the user connects to your website via another browser, another cookie will be added to this new browser with the user’s consent. If cookies are refused (by default or explicit refusal), there is no recognition. Similarly, if cookies are regularly deleted, the visitor is considered a “new visitor” on each visit after the deletion.

In the case of user rejection of cookies, fingerprinting can still be used to obtain information about the visitor and mark their browser, but this solution is in contradiction with several principles set out in the GDPR.

  • Relevance: if the browser is recognized, the visitor is not. In the case of a family computer, three visits recorded via the same browser can come from three different people. Let’s take the example of a family of three, a couple and their son. Everyone visits the same musical site via Firefox: one of the parents loves reggae and is looking for old Steel Pulse tunes, the other loves Stromae, and junior is only into Daft Punk… Here the visitor profile that will be assigned later will be less relevant, because cookies will not make the distinction between the three individuals…
  • Respect for privacy: Cookies allow the recognition of a web browser for a maximum period of 13 months, subject to the user’s explicit agreement.

#Database cross-recognition system: this is the system used by the Adexchange and DMP for advertising management, but we also have the recent example of large companies signing partnerships with social networks. In principle, a company will be able to cross-reference its database with another company’s database to enrich the profile of its users or generate new contacts. However, this process is again only possible with the explicit consent of the user for each potential use of their data. They must be clearly informed of these partnerships and consent individually to the sharing of their data with each actor involved. This procedure is very difficult to set up and this recognition system is often problematic.

  • Relevance: Relevance here is inversely proportional to privacy.
  • Respect for privacy: this practice is theoretically only possible by obtaining the user’s consent to share their data with each actor involved.

In summary, effective multi-channel analysis relies essentially on visitor recognition across multiple channels and hardware interfaces. To do this, it uses various tools such as cookies, account creation or database cross-referencing. This recognition is very difficult to obtain in a comprehensive way, except by using systematic identification of the visitor (site accessible only after log-in for example) or procedures that are more or less in contradiction with the principles of confidentiality and respect for privacy that surround the GDPR.


 *An English translation of the French “Ce qui se conçoit bien s’énonce clairement”, written by the 17th century French poet Nicolas Boileau-Despréaux

Author

Knowledge Manager After On-the-job and Off-the-job training in purchasing and management at Carrefour, and sales training at Procter & Gamble, JM evolved in the mass retail sector in top management positions for large hypermarket, central purchasing and logistics groups, with an expatriate experience in Africa as a Central Director. In late 1995, JM created an Internet start-up company and after three years (late 1998) he joined Alain Llorens and the AT Internet team where he took up his position in sales, and was also at the heart of the pioneering adventure in Web analytics. At 55 and after almost 13 years seniority in the company, JM has been Knowledge Manager since 2009.