When customers visit Amazon, 65% said they don’t even notice the ads featured, while 25% find them “useful or relevant,” according to the “2018 Amazon Shopper Behavior Study: How Shoppers will Browse and Buy on Amazon,” a report from CPC Strategy.
According to the data, Amazon continues to improve its native advertising experience for shoppers, a move that ensures the company is helping consumers to find the right product, for the right price, at the right time. It also means additional digital ads are not paramount to driving sales.
For example, more than 50% of Amazon shoppers aren’t willing to go beyond the second page when searching for a product. Meanwhile, they are more open to trying new products, as 80% are open to “occasionally” or “frequently” trying new products or brands on Amazon. This is a huge jump from 50% last year. And customer reviews are not spurring this curiosity, as approximately 80% of these customers don’t entirely trust Amazon’s customer reviews.
Despite Amazon being their “go-to” shopping source however, 74.8% of Amazon shoppers still price check on other sites.
When customers are ready to make a purchase with Amazon, more shoppers are open to using voice-enabled devices. In fact, 14.2% of Amazon customers made a purchase via a voice-enabled device in the last six months, and 61.3% of voice-enabled device owners have an Amazon Dot or Echo, the study said.
“We expected that some Amazon shoppers owned Amazon’s voice enabled devices, and had made purchases using Alexa, but we weren’t prepared to see numbers like this so early into the game,” said Nii Ahene, COO and cofounder of CPC Strategy. “The battle for ultimate marketplace dominance isn’t over, but Amazon is off to an early lead.”
From previous Facebook IQ automotive research in the US and Brazil, we know that mobile is helping to drive a shift in the auto path to purchase. Whereas people may have once relied solely on dealer information, they can now check their smartphones while on the go and use friends, family and social media as resources and to help them gather intel. But what’s happening in Europe? What is the impact of mobile on the car purchase journey in France, the UK and Germany? With almost half of European smartphone users spending three or more hours on their mobile device each day,1European car brands would benefit from understanding the opportunities and challenges this presents.
Facebook IQ conducted a three-pronged study to understand how car buyers now shop. Firstly, we commissioned GfK to survey 1,500 people in the UK, France and Germany, who had either bought a new car in the prior 12 months (buyers) or who said they are looking to buy a car in the next months (in-market shoppers). Then GfK looked at historical laptop and mobile data for 50 UK in-market shoppers and 50 UK buyers. And finally, they conducted face-to-face interviews with 20 in-market shoppers and buyers in the UK.
We discovered that the process of buying a car is a multi-screen and social activity, and that brand and features, not offer price, can be more of a determining factor when it comes to choosing a car.
The auto path to purchase is a multi-screen journey
Our research revealed that a path to purchase a vehicle in Europe lasts up to 24 weeks, spans five distinct phases across devices and happens both on- and offline.
Car buyers used to begin their search for a car at a dealership, but today they tend to visit a dealership only after they’ve settled on two or three brands and models. Many in-market shoppers said they use their mobile phones to find inspiration, for example, over a third of people (34%) said they use their smartphone to browse visual content related to cars from other consumers. When it comes to research, laptops and desktops are the dominant device, with 69% of in-market shoppers saying they use their laptop/desktop for conducting research on manufactures websites.2
The automotive path to purchase in Europe spans five phases2
Each of these phases afford automotive brands the opportunity to potentially engage with and influence in-market buyers in a relevant way. For example, during the qualifying consideration phase, an in-market shopper tended to select 3-4 brands to explore more later, so that’s a potential window where your brand could help her shorten her list. Later, she’ll likely be looking for support to help her ensure choices of model, features and financing are the right ones for her. If you communicate with your in-market buyers in the right way at the right time, you reduce the risk of being seen to bombard them.
I made an inquiry about a car and have not been left alone by the company since. If I want more information I will gladly ask for it, please stop sending me emails and calling me. When I am ready to make a purchase I will make the calls.
Adele, 33 years old
When we asked people about the source they consulted while considering their purchases, the top sources ranked fairly evenly — from friends and family (31%) to car reviews and news sites (30%), from manufacturer/brand websites (37%) to dealer websites (32%).2
The online monitoring in the UK, showed six in ten of the 50 media-tracked UK in-market shoppers browsed Facebook while conducting their research, and of these, most (72%) do so on mobile. These 50 in-market shoppers visited Facebook, on average, 44.7 times in the month prior to purchasing a new car, Instagram 6.9 times and the manufacturers sites 5.4 times.4
Think brand and features — not price
When we asked which were the most important features influencing a car purchase decision, we can see that brand and features tend to determine what cars people buy, whereas the offer and the dealer are far less important. Perhaps buyers are less reliant on dealers than they once were, as they can get accurate, frequently updated information just by checking their smartphones.
Brand/make and model of car were cited as the most important purchase influencing factors3
Friends and family are more influential than dealers
So, who or what is influencing the decision to purchase a car? As we highlighted earlier, our research shows that 31% of respondents said they rely on the advice of friends and family during the consideration phase of their purchase journey.2 How do they get this advice? Some 40% of media-tracked UK respondents use Facebook to reach out to family and friends.4
If we look closer at the influence of friends and family, we find the network of influence is wide, but that the key influencers are closely connected to the person buying the car. For example, our survey found that a person’s partner is 1.68X more influential, and friends are 1.63X more influential, than a dealer.
The friends and family network is wide, but key influencers are close1
What it means for marketers
Keep conversing with in-market shoppers.
People settle on two or three brands and models early in the path to purchase, so an always-on approach is important to drive awareness and consideration. With so many automotive conversations taking place on social and with friends and family, brands should think about how they can keep having conversations with in-market shoppers throughout the year, not just during periods like product launch.
Make the most of multi-screen.
The new path-to-purchase — fueled by online research and social media — opens up new opportunities. Auto brands now have the opportunity to combine the best aspects of a visit to a dealer — personalization, customization, information exchange — with the powerful targeting, relevancy and reach of online.
Measure and optimize.
People-based marketing can help empower automotive marketing teams to engage with in-market buyers based on the intent those buyers have shown online, including on mobile devices, which are largely invisible to standard online cookie-based tracking methods. Find out more about how to use the Facebook Pixel, which makes conversion tracking, optimization and remarketing easier.
I feel fortunate to have followed some of the amazing major changes in digital marketing and technology over the last 15 or 20 years. I’m sure you will have enjoyed living through, following and acting on these changes too. Looking back, we’ve seen a phenomenal growth in the importance of organic, then paid search, then social media and more recently, incredible worldwide growth in mobile and particularly smartphone usage.
As well as this article, to help Smart Insights members, we also have a more detailed free download of the marketing megatrends, which are 9 digital marketing and martech megatrends that will help give you an edge in 2017.
Download free member resource – Digital Marketing Megatrends 2018
Learn how to get an edge in 2018 by deploying the latest marketing techniques that businesses of all types need to consider to stay competitive.
Looking forward, in this article, I’m going to review 10 new trends which I believe, based on my experience consulting and training, are relevant for marketers across businesses of a range of sizes. But, first, I’m interested to know what you think will be important to you and your business in 2018.
Which marketing trend will be most important to you and your business in 2018?
We have asked this question over the past few years and it’s been really interesting to see what ‘rocks your digital world’ since there are some common themes amongst the top 3 and some activities surprisingly low. The question we asked was around the most important commercial trends. We had around 850 votes from marketers in different types of business from around the world. Thank you if you voted! Here’s what you thought:
By asking for just one technique from many, this helps shows the top 3, 5 or 10 top-level trends. There are a clear top three techniques, each over 10%, but with a long tail of many other techniques showing the potential for optimising different areas of digital marketing. Let’s take a look at the top three…
It’s no surprise to see content marketing ‘top of the pile’ since this has been in the top three for each of the years we have run this poll. We see content marketing as the ‘engagement’ fuel that powers all digital communications from search to social to email marketing to creating website experiences which convert. Our content marketing toolkit is popular since members want to learn a more planned approach to mapping content against personas across the customer journey.
More of a surprise is that Big Data is in second position. I think this is because marketers are aware of the potential of using data as what we call ‘actionable insight’. To help the decision on which technique to choose, we expanded upon the short labels you see in some polls to help scope the response more carefully. ‘Big Data’ is a nebulous term, but when we expanded the definition to include insight and predictive analytics, it shows the value of the specific marketing techniques for Big Data and this help explains why this is in position number two.
In third position is Artificial Intelligence and Machine Learning. We added this to the poll this year with the interest in it and it’s ‘straight in at number three’! It’s good to see the interest in these techniques which we have been covering a lot on the blog and in our member resources this year. In trend 8 we show how different AI techniques can be mapped against the customer lifecycle.
Here is the full listing of digital marketing techniques:
Big Data (including market and customer insight and predictive analytics)
Wearables (e.g. Apple Watch, activity trackers, augmented reality)
The ten marketing trends to act on in 2018
If you look at the 14 themes that we covered last year, none of these top-level marketing techniques are especially new, so it’s difficult to describe them as new trends or innovations. However, techniques like Big Data and analytics, Content Marketing and Email/Marketing Automation have continued to grow in importance and will be used by many businesses.
So in my look at the trends this year, I’ll be looking at integration as the theme. In our research on managing digital marketing (another free member download) you can see that only 6% of companies thought their integration process was completely optimised, yet many are actively working on integration.
Integrated marketing communications or IMC isn’t a concept you see written about much on blogs or social media since it’s high-level with everyone getting excited at the latest minor innovations from the frightful 5 – at the time of writing we’re getting excited about the Animojis in iPhone X for example. Fun, but they’re not going to help deliver the most relevant message and offer for an individual, which is the aim of IMC.
So, let’s take a look at the 10 trends. You’ll notice that in a lot of these predictions, I’ll refer to Artificial Intelligence and Machine Learning. It’s what I see as the biggest trend to consider in the year ahead. There has been a lot of hype around it in 2017 and we’re starting to understand the opportunities. In 2018 it will become more about selecting solutions and implementation.
Trend 1. Integrating Marketing Activities Into the Customer Lifecycle
Given the way the complexity of marketing and digital marketing has increased, techniques like customer journey mapping for different personas are increasing in importance to help define the most relevant communications and experiences for different touchpoints in the customer journey.
To support this, the way I like to think about how to improve the effectiveness of digital marketing is to think from the customers’ viewpoint of the communications opportunity available through the customer lifecycle for different types of business.
We define lifecycle marketing as:
Creating a managed communications or contact strategy to prioritise and integrate the full range of marketing communications channels and experiences to support prospects and customers on their path-to-purchase using techniques such as persuasive personalised messaging and re-targeting.
We designed this mind-tool to help members think through all the potential touchpoints across paid, owned and earned media. Then you can perform a ‘gap analysis’ of the use and effectiveness of lifecycle comms you are using against those you could be using to increase the relevance and response of communications.
Trend 2. Integrating personalization into the user journey / customer experience
To increase relevance and response of comms, website personalization has been widely used within transactional ecommerce sectors like retail, travel and financial services for a long time now.
More recently, lower cost options have become available with different types of solutions. There are many forms of web personalization varying from those integrated into content or commerce management systems; those integrated into analytics solutions or standalone Software as a Service (SaaS) personalization options that integrate with your CMS and analytics. A useful method to review your use of personalization at the top-level is this experience personalization pyramid:
The three levels shown in the chart are:
1. Optimization. Structured experiments. AKA AB Testing or Multivariate testing. Google Optimize is an example of one of these services that launched in 2017.
2. Segmentation. Target site visitor groups, each one with specialized content to increase relevance and conversion.
Each one still requires separate manual rules and creative to be set up. So returns for this approach eventually diminish after the maximum sustainable number of audience segments has been reached.
3. 1-to-1 Personalization. Using Artificial Intelligence (AI) technology to deliver an individualized experience to each customer. 1-to-1 employs some of the same principles as optimization and segmentation, but by offering a solution to their two greatest limitations-delayed results and inability to scale-it represents a fundamentally different approach.
So, the main trend within personalization is increased use of artificial intelligence rather than manual rules. Plus, we can also expect to see Website personalization services being adopted across more sectors than the transactional sectors it has become popular within.
Trend 3. Integrating machine learning into marketing automation
Personalization can also be applied across the lifecycle in email comms. Yet, our research on email marketing shows that despite the widespread use of email and marketing automation systems, many companies don’t manage to put in place a full lifecycle contact system like that shown in the lifecycle visual above.
We assessed segmentation and targeting of emails based on the number of criteria that are used from none at all up to dynamic content.
The findings from our State of Email marketing report are shocking: Half (50%) don’t use any targeting whatsoever, less than a third (29%) use basic segmentation for targeting and less than 15% use segmentation and personalization rules to reach specific audiences within their database. This means that they may be missing out on opportunities for automated emails with dynamic content for welcome and nurture of prospects and customers.
Although email marketing automation is another technique where artificial intelligence and machine learning is being applied more often. Using machine learning offers opportunities to automate targeting as it does for web personalization. However, personalization is potentially more difficult since emails, by their nature, have more complex creative. This data suggests to me that many businesses aren’t ready for AI and machine learning within email marketing and they need to deploy fundamental triggered automation features first.
Trend 4. Integrating social messaging apps into communications
The increasing use of messaging apps is a trend we have mentioned in previous trends round-ups. According to the latest Ofcom Communications Market research more than half of the total mobile audience used Facebook Messenger (61%) and half used WhatsApp (50%). Both properties are owned by Facebook. The Snapchat mobile app had a reach of 28%, with 10.1 million unique visitors.
Trend 5. Integrating video into the customer journey
Video is also increasing in popularity fuelled by social . This breakdown of Google popularity shows the dominance of YouTube. We used to say that YouTube was the second biggest search engine, but this data shows that it is now more popular than Google Search based on number of users in a given month (this research also from the comScore panel via Ofcom).
This visual reminds us of the opportunities to use video marketing through the customer lifecycle from pre-roll ads in YouTube (just one option, Google has 10 Video ad options), explainer ads on site and retargeting through video.
Augmented and Virtual Reality are closely related to video engagement, but although we’ve been tracking these, we have seen fewer examples and case studies this year. So, do let us know of any examples.
Trend 6. Integrating content marketing into the customer journey using a customer engagement strategy
Video is just one type of content, albeit important. In previous polls about the technique that will give the biggest uplift in future, content marketing has been popular, in the top one or two in the list.
The trend I’m seeing here is that businesses are getting serious about treating content as a strategic resource, that means developing a customer engagement strategy using different media as shown in the lifecycle diagrams above, and at a practical level, developing content for different audiences using techniques like Personas and Content mapping. Our research shows that these customer-centric analysis techniques are growing in importance, which has to be a good thing for consumers and businesses!
Trend 7. Integrating search marketing into your content marketing activities
If we look at the top digital sales channels, search marketing is dominant. Social media is far behind in most sectors, despite its ongoing popularity with consumers. We now know that in many sectors social media can be a great tool for engaging audiences with a brand and improving favourability and awareness, but it typically doesn’t drive lead volume or sales. So I haven’t given social media it’s own section, although integrating it with other channels like web, search and email marketing remains relevant. See our recap of SMW London for the latest social media trends.
However, within search marketing there is today relatively little innovation that we get to hear about compared to the past. Looking at natural search shows that the Moz algorithm change history has no entries since the non-specific ‘Fred’ update in March, whereas in previous years it would have had 5+ with new updates to Panda and Penguin. This is partly down to Google sharing less, with Matt Cutts no longer actively evangelising, although updates are available from John Mueller in their Search team.
Within organic search, one trend I think marketers should be aware of is the changing face of the SERPs as shown by the Mozcast SERPs features update which shows the types of links within a bundle of top 10k keywords they monitor.
It shows the importance of techniques such as Knowledge Panels (important for brands and local businesses); Related questions; featured / rich snippets / quick answers and reviews. We have found that the way these vary across the top 3 to 5 positions can make a big difference in the volume of visits from informational searches.
Within AdWords, referencing Google’s list of new features shows more innovation. Much of it is around reporting compared to new ad features for mobile in previous years, but there are some new options like with Enhanced CPC (ECPC) bidding and Smart Display campaigns. This is an example of Google deploying different types of machine learning including Automated bidding Using Target CPA as a basis; Automated targeting which means your ads increasingly show where they’ll get you the most business and automated ad creation from the building blocks you provide, like headlines, descriptions, logos and images.
Our own digital marketing tools wheel seeks to simplify this, but has over 30 categories of insights and automation tools which shows the challenge of integrating marketing technology. The trend here is that there is no let up in tools offering innovative methods to analyse or automate. Our final two categories highlights some of these.
Given the plethora of martech, the most apt definition seems:
‘very large amount of something, especially a larger amount than you need, want, or can deal with‘
You might expect there would be a trend to increasing use of marketing clouds, but our research suggests there isn’t widespread adoption of these.
This challenge was highlighted to use recently in our members’ Facebook group where a member asked about tools for integrating insights from different paid media ad serving tools which can give the best results if managed separately, for example, Facebook, Twitter, LinkedIn ads and Google AdWords. Rivery.io is a new option that has launched recently, that should do well. The trend here is new integrated media insights tools other than Google or Adobe, which can help you compare performance of different media.
These services are surprisingly expensive, particularly since they are additional analysis tools. They’re not martech that directly increases leads or sales to the business. For example, I was recently recommended this service (Funnel.io ) that costs a minimum of $200 / month, even if it’s solely used to integrate data from multiple sources into Google Sheets. It’s a lot when to get the value from these tools you have to ringfence time so that the analytics are reviewed and acted on sufficiently.
Trend 10. Integrating digital marketing insights sources
Our digital marketing tools wheel contains many free and paid sources of insight about your digital marketing. Here, I’m talking specifically about services which help you stay up-to-date. We’re avid users of these services since they help us keep readers up-to-date via our own blog, twice weekly newsletters and monthly What’s Hot feature.
In a recent article on keeping marketing teams up-to-date, Mark Kelly explains that we recommend using Feedlyas a way of aggregating primary marketing news sources via RSS. Plus, I recommend taking a look at Zestwhich is a Google Chrome extension, new in 2017, which I and the team at Smart Insights use and is well worth checking out. Its curated content is specifically designed for and updated by marketers. Like Feedly, you can use it to review the most useful content recommended by ‘the crowd’, in this case ‘your tribe’ of marketers.
In a world where physical and virtual environments are rapidly converging, companies need to meet customer needs anytime, anywhere. Here’s how.
Many of the executives we speak with in banking, retail, and other sectors are still struggling to devise the perfect cross-channel experiences for their customers—experiences that take advantage of digitization to provide customers with targeted, just-in-time product or service information in an effective and seamless way.
This quest for marketing perfection is not in vain—during the next five years or so, we’re likely to see a radical integration of the consumer experience across physical and virtual environments. Already, the consumer decision journey has been altered by the ubiquity of big data, the Internet of Things, and advances in web coding and design.1Customers now have endless online and off-line options for researching and buying new products and services, all at their fingertips 24/7. Under this scenario, digital channels no longer just represent “a cheaper way” to interact with customers; they are critical for executing promotions, stimulating sales, and increasing market share. By 2016, the web will influence more than half of all retail transactions, representing a potential sales opportunity of almost $2 trillion [≈ California GDP, 2011].2
Companies can be lulled into thinking they’re already doing everything right. Most know how to think through customer search needs or have ramped up their use of social media. Some are even “engineering” advocacy—creating easy, automatic ways for consumers to post reviews or otherwise characterize their engagement with a brand.
Yet tools and standards are changing faster than companies can react. Customers will soon be able to search for products by image, voice, and gesture; automatically participate in others’ transactions; and find new opportunities via devices that augment their reality (think Google Glass). How companies engage customers in these digital channels matters profoundly—not just because of the immediate opportunities to convert interest to sales but because two-thirds of the decisions customers make are informed by the quality of their experiences all along their journey, according to research by our colleagues.3
To keep up with rapid technology cycles and improve their multiplatform marketing efforts, companies need to take a different approach to managing the consumer decision journey—one that embraces the speed that digitization brings and focuses on capabilities in three areas:
Discover. Many of the executives we’ve spoken with admit they are still more facile with data capture than data crunching. Companies must apply advanced analytics to the large amount of structured and unstructured data at their disposal to gain a 360-degree view of their customers. Their engagement strategies should be based on an empirical analysis of customers’ recent behaviors and past experiences with the company, as well as the signals embedded in customers’ mobile or social-media data.
Design. Consumers now have much more control over where they will focus their attention, so companies need to craft a compelling customer experience in which all interactions are expressly tailored to a customer’s stage in his or her decision journey.
Deliver. “Always on” marketing programs, in which companies engage with customers in exactly the right way at any contact point along the journey, require agile teams of experts in analytics and information technologies, marketing, and experience design. These cross-functional teams need strong collaborative and communication skills and a relentless commitment to iterative testing, learning, and scaling—at a pace that many companies may find challenging.
Let’s consider what an optimized cross-channel experience could look like when companies target improved capabilities in these three areas.
A new normal …
Imagine that a couple has just bought its first home and is now looking to purchase a washer and a dryer. Mike and Linda start their journey by visiting several big-box retailers’ websites. At one store’s site, they identify three models they are interested in and save them to a “wish list.” Because space in their starter home is limited—and because it is a relatively big purchase in their eyes—they decide they need to see the items in person.
Under an optimized cross-channel experience, the couple could find the nearest physical outlet on the retailer’s website, get directions using Google Maps, and drive over to view the desired products. Even before they walk through the doors, a transmitter mounted at the retailer’s entrance identifies Mike and Linda and sends a push alert to their cell phones welcoming them and providing them with personalized offers and recommendations based on their history with the store. In this case, they receive quick links to the wish list they created, as well as updated specs and prices for the washers and dryers that they had shown interest in (captured in their click trails on the store’s website). Additionally, they receive notification of a sale—“15 percent off selected brand appliances, today only”—that applies to two of the items they had added to their wish list.
When they tap on the wish list, the app provides a store map directing Mike and Linda to the appliances section and a “call button” to speak with an expert. They meet with the salesperson, ask some questions, take some measurements, and close in on a particular model and brand of washer and dryer. Because the store employs sophisticated tagging technologies, information about the washer and dryer has automatically been synced with other applications on the couple’s mobile phones—they can scan reviews using their Consumer Reports app, text their parents for advice, ask Facebook friends to weigh in on the purchase, and compare the retailer’s prices against others. Mike and Linda can also take advantage of a “virtual designer” function on the retailer’s mobile app that, with the entry of just a few key pieces of information about room size and decor, allows them to preview how the washer and dryer might look in their home.
All the input is favorable, so the couple decides to take advantage of the15 percent offer and buy the appliances. They use Mike’s “smartwatch” to authenticate payment. They walk out of the store with a date and time for delivery; a week later, on the designated day, they receive confirmation that a truck is in their area and that they will be texted within a half hour of arrival time—no need to cancel other plans just to wait for the washer and dryer to arrive. Three weeks after that, the couple gets a message from the retailer with offers for other appliances and home-improvement services tailored toward first-year home owners. And the cycle begins again.
… requires new capabilities
As this example makes clear, the forces enabling consumers to expect real-time engagement are unstoppable. Across the entire customer journey, every touchpoint is a brand experience and an opportunity to engage the consumer—and digital touchpoints just keep multiplying. To maximize digital channels, companies need to focus on improving their “3-D” capabilities.
Discover: Build an analytic engine
Even in this era of big data and widespread digitization of customer information, some companies still lack a 360-degree view of the people who buy their products and services. They typically measure the performance of direct sales activities such as product pitches and encourage downloads using “last-action attribution” analyses, which assess campaigns in isolation rather than in the context of the entire cross-channel consumer decision journey. Usually these data will have been stored in disparate locations and legacy systems rather than in a central server. Complicating matters further is the range and quantity of unstructured data out there—information about consumers’ behaviors and preferences that is, for instance, captured in online reviews and social-media posts. In our experience, this type of data is usually the least understood and therefore the least utilized by companies.
To get the full customer portrait rather than just a series of snapshots, companies need a central data mart that combines all the contacts a customer has with a brand: basic consumer data plus information about transactions, browsing history, and customer-service interactions (for an illustrative example of how companies can lose potential customers by failing to optimize digital channels, see exhibit). Tools like Clickfox and Teradata can help marketers gather these data and begin to pinpoint opportunities to engage more effectively with consumers across the decision journey. This collection effort requires input from people across multiple functions—a complex undertaking, to be sure, but the payoff can be big. Our work in this area suggests that the growth rate of earnings before interest, tax, depreciation, and amortization of grocers that focus on customer analytics is 11 percent, compared with just 3 percent on average for their main competitors. For big-box retailers, the difference is 10 percent compared with 2 percent.4
With a comprehensive data set in hand, companies can undertake the sort of quick-hit “shop diagnostics” that many tell us is lacking in their marketing and e-commerce programs. Using analytic applications such as SAS and R, and by applying various algorithms and models to longitudinal data, companies can better model the cost of their marketing efforts, find the most effective journey patterns, spot potential dropout points, and identify new customer segments. Based on its analysis of click-through behaviors, for instance, one regional retailer saw that a particular set of customers preferred digital shopping over physical and always read e-mail on Saturdays, and so the retailer altered its e-mail campaign to send this cohort online offers only on Saturdays.
Additionally, by using business-process software and services from vendors such as Adobe Systems, ExactTarget, Pegasystems, and Responsys, companies can identify in real time the basic “triggers” for what individual customers need and value—regardless of the product or service—and personalize their approach when making cross- or up-sell offers. They can also use these tools to generate automated reports that track customer trends and key performance indicators. For instance, the regional retailer’s analytics suggested that two of the customers who read their e-mail only on Saturdays were in the midst of a career change; both had revised their profiles on LinkedIn within the past three days. Based on its analytics efforts, the company was able to create targeted offers for each—one received information about laptop bags (based on her previous purchases) while the other received information about suits (based on his previous purchases).
Already, the companies employing these types of advanced analytics have seen significantly improved click-through rates and higher conversion rates (between three and ten times the average). Additionally, McKinsey analysis shows that using data to make better marketing decisions can increase marketing productivity by between 15 and 20 percent—that’s as much as $200 billion ≈ cost of NASA Space shuttle program
≈ Annual credit card fraud as of 2009
≈ cost of San Francisco 1906 earthquake
≈ all real estate in Brooklyn, NYC, 2010
“>[≈ UN estimated cost to end world hunger, 2011] given the average annual global marketing spend of $1 trillion ≈ Value of US natural gas reserves”>[≈ Public US health care spending, 2005].5
Design: Create frictionless experiences
Careful orchestration of the consumer decision journey is incredibly complex given the varying expectations, messages, and capabilities associated with each channel. According to published reports, 48 percent of US consumers believe companies need to do a better job of integrating their online and off-line experiences. There is a premium for getting this right. One major bank unlocked more than $300 million in additionalmargins by making better use of digital channels. It tapped into underutilized customer data and delivered targeted marketing messages at various points in the purchase-decision process. The bank used the data, plus various personalization and testing tools, to inform changes in marketing campaigns for certain product lines; every next step for every customer was progressively tailored to help the customer take the best action.
Digital natives such as Amazon, eBay, and Google have been leading the pack in resetting consumers’ expectations for cross-channel convenience. (Think of eBay’s Now mobile app, which provides one-touch ordering from any of eBay’s retail partners and same-day delivery in some US cities, or Amazon’s recent incorporation of a help button in the company’s latest-generation Kindle Fire tablet, linking users to a live help-desk representative.) These players have perfected the ability to test new user experiences and constantly evolve their offers—often for segments of one.
This lean, start-up approach might sound counterintuitive to large, entrenched marketing organizations in which decisions are made at a snail’s pace, but test-and-learn methods can help companies decide how best to optimize (and customize) critical design attributes of the consumer decision journey at various points along the way. In the appliances example discussed earlier, the retailer’s customer analytics allowed it to design an experience for the couple that was completely customized to their context—from their initial online searches to their physical and virtual interactions at the store and to their follow-up with the company postpurchase. Rather than push what could be construed as intrusive (even creepy) messaging, the retailer provided Mike and Linda with the most useful information at every point in their decision journey and offered the easiest possible path to purchase and delivery.
To create similarly frictionless experiences, some companies have created 24/7 digital “window shops” to test product ideas and customer interactions and collect rapid feedback without the need for additional labor or inventory. Several companies that offer inherently complex products or services have incorporated “gaming” elements into their experiences—tweaking the navigation, content architecture, and visual presentation to allow consumers to trade off and test various options and prices associated with a product before making a decision. One financial-services firm redesigned its mobile app for collecting credit-card applications to incorporate the customer context. Previously it had a one-size-fits-all interface; in the redesigned version, various elements of the mobile app’s interface—such as pricing, stage of process, and designated credit limits—are dynamically generated based on existing customer information. And the app’s page layout and navigation are rendered simply, allowing for easy completion within just a few clicks. The result has been a significant uptick in online applications.
Deliver: Build a more agile organization
In our experience, too many companies are afraid to launch “good enough” campaigns—ones that are continually refined as customers’ purchase behaviors and stated preferences change. Under the direction of conservative senior leaders, teams tend to launch campaigns that take too long to get off the ground and end up revealing few new insights. Instead, they must be willing to conduct lots of small-scale experiments with cloud or proxy website services to pilot new designs and prove their value for investment.
These types of agile, data-driven activities must be supported by an organization that has the right people, tools, and processes. Many companies will have some of the talent required, but not all, and executives will inevitably face resistance when it comes to introducing lean tools and techniques into their sales, marketing, and IT processes. The most successful omnichannel marketers we’ve seen have established centers of excellence in both analytics and digital marketing, and they practice end-to-end management of microcampaigns. Their campaign-building processes typically include systematic calendaring, brainstorming, and evaluation sessions to allow for one-week and two-week turnaround times. And roles and responsibilities are clearly defined. Far from creating a rigid, hierarchical process, this model frees up individuals to iterate quickly—what is sometimes called “failing fast forward” in the world of high tech.
At one bank, for instance, business-unit leaders gather each month to talk about their progress in improving different consumer journeys. As new products and campaigns are launched, the team places a laminated card illustrating the journey at the center of the conference-room table and discusses its assumptions about the flow of the experience for different segments and about how the various functional groups need to contribute: Where does customer data need to be captured and reused later? How will the design of the campaign flow from mass media to social media and then on to the website? What is the follow-up experience once a customer sets up an account? The team has also appointed dedicated mobile and social-media executives to become evangelists for strengthening the omnichannel experience, helping business units raise their game along a range of consumer interactions. The company’s first wave of fixes and new programs generated tens of millions of dollars in the first six months, and the team expects it to continue scaling beyond $100 million [≈ Large city office building] in added annual margins.
Building an agile marketing organization will take time, of course. Companies should start by assembling a “scrum team” that will bring the right people together to test, learn, and scale. The team should incorporate cross-functional perspectives (marketing, e-commerce, IT, channel management, finance, and legal), and its members must adopt a war-room mentality—for instance, making tough calls about which campaigns are working and which aren’t, and which messages should take priority for which segments; launching new tests every week rather than every six months; and mustering the IT and design resources to create content for every possible type of interaction.
Companies likely will need to hire people with skills that differ from the ones they rely on now. Some organizations have developed innovative, venture capital–like strategies for finding and recruiting the people they need. Staples, for instance, has built an e-commerce innovation center in Cambridge, Massachusetts, to better recruit technology talent from nearby Harvard University and MIT, and it recently bought conversion-marketing start-up Runa to act as a talent hub on the West Coast.
New types of information systems may also be required. The best technology solutions will vary according to a company’s starting point and objectives. Generally, though, companies will get the best results from tools that enable large-scale data management and the integration of databases; the generation of next-best-action and other types of advanced analyses; and simpler campaign testing, execution, and metrics.
Companies need to make strategic decisions about the best pathways to build customer value. Many cite digital as one of their top three priorities in this regard, but few have taken the time to measure the level of digital maturity their organization has achieved. A company’s digital quotient (DQ) is a function of how well defined its long-term digital strategy is, its effectiveness in implementing that strategy, and the strength of its organizational infrastructure and information technologies. The companies that incorporate the notion of DQ into their short list of performance metrics can more effectively monitor their progress across the digital capabilities we’ve outlined here, enabling more targeted investments and accelerated rates of digital growth.
Indeed, the companies that ultimately succeed in omnichannel marketing and sales will likely resemble tech companies and, interestingly, publishers—effectively using big data and digital touchpoints to drive growth and reduce costs, while producing and managing a variety of content (catalogs, coupons, web pages, mobile apps, and user-generated content) in real time across multiple platforms to create breakthrough customer experiences. This means rethinking the analytics that inform their segmentation strategies, the flow of the experiences they design, and the way they set up their internal operations for faster iteration and delivery of service.
Digital technologies and advanced analytics have the potential to create the Invisible Bank of the future. Powered by artificial intelligence (AI) and activated by voice, virtual banking assistants can become an integral part of our daily lives.
Banking today is becoming less and less a place you go, and more something that is hidden from view behind digital banking and commerce apps. Once an account is opened at a bank or credit union, there is less need to stop into a branch, since functions like deposits, borrowing, payments and transfers can be done without personal interaction through online and mobile devices.
Fueled by improvements in advanced data analytics, artificial intelligence (AI), voice-controlled devices, application programming interface (API) and cloud technology, the Invisible Bank will be able to be integrated seamlessly within a consumer’s everyday life. Ultimately being available ‘beyond the device,’ these technologies will allow banking, commerce, daily intelligence and decision making to be available to consumers 24/7/365 as a virtual, e-personal digital concierge.
“Banking in the background is the future,” states Brian Roemmele, founder atPayfinders.com. “The more a personal assistant knows about a consumer and daily ‘life patterns’, the better it can interact with millions of financial (and non-financial) options at any given moment.”
Warren Mead, fintech lead at KPMG UK, said, “Banks are making efforts to improve customer service through use of exciting technologies like robotics, artificial intelligence and blockchain. But, the pace of change is slow and in reality, I’d say banks are only 10% of their way through their digital transformations.”
Disappearance of Banking as We Know It
KPMG’s vision for the Invisible Bank of 2030 is a disaggregated industry – with three distinct components.
The first layeris the platform, leveraging a Siri-like device that combines all of the many other services provided by smart tech with banking
The second layer is the product, which becomes more flexible and customer-centric
The third layer is the process layer that brings a new wave of utilities to operate the transactional infrastructure of banking
According to the vision presented by KPMG, large parts of the traditional banking organization could disappear. Functions and operations like customer service call centers, branches and sales teams could be a thing of the past. According to KPMG, the winners will be those that are best positioned to utilize their data, drive down costs, build effective partnerships with a broad range of third parties, and drive this new engagement with a robust cybersecurity infrastructure.
“Getting most banks to our vision of 2030 will be painful,” states the report. “Currently, technology firms invest 10-20% of revenues into research and development, for banks it’s just 1-2%. With banks’ return on equity under 5% it’s hard to see that changing significantly in the short to medium term, but if firms want to remain relevant, it has to.”
“Banking has not reached the SKU-like level of product and service structure. Amazon is the example of a marketplace where SKU level of product search and recommendation is available at one location. Once Voice Assisted AI and taxonomy identifying all banking functions are available to anyone at any moment, it will move banking into a new realm.” – Brian Roemmele
The Invisible Bank will be buried within a broader, more digital, connected way of life. Consumers will interact with a personal digital assistant (like Siri or Alexa) that proactively performs daily personal and financial tasks, informed by insights gathered from structured and unstructured data. The role of banking may be as a centralized provider of financial services from a variety of providers, as presented by Ron Shevlin (“The Platformification of Banking“). In a worst case scenario banking could become relegated to the position of a white labelled product provider.
To illustrate its vision for banking in 2030, KPMG presented EVA (Enlightened Virtual Assistant), made possible by advanced data analytics, voice authentication, artificial intelligence, connected devices, application programming interface (API) and cloud technology. It was made clear that all of these technologies are available today and merely need to be combined and enhanced to make KPMG’s EVA a reality.
The example of a day with EVA involved the assistant accessing payment data to notice changes in spending patterns (in this case an increase in junk food spending). Using this insight collected over a period of time, EVA suggests a yoga class prior to booking and paying for it. Leveraging social media insight, EVA even suggested friends that might be interested in the same class.
The virtual assistant then recommends buying a gift for a business associate and proactively conducts some basic banking tasks that benefit the user. In this example, EVA shifts savings to get a better interest rate and took action on an unexpected charge by asking for a reversal of the charge with the bank.
With the EVA vision, there is no ‘banking app’ as we know it today. In fact, visiting a bank would be as foreign as using a dial-up modem or landline phone.
Access will be authenticated with biometric voice recognition, with banking insights being integrated with health, diary, social and other parts of the consumer’s daily life. The potential to integrate with IoT innovations is also endless.
According to KPMG, this platform layer will probably be provided by global technology players like Amazon, Google, Apple and/or Facebook. This is because technology hardware is hardly the core business of banks today who are focused on maintaining costly and outdated legacy infrastructure.
Progressive banks will want to own the product layer, however. This includes today’s traditional products, the consumer’s account behavior, custody of assets, and security function in addition to being the provider of outside products and services provided by fintech and non-financial technology providers.
The biggest banks will also want to retain the transactional (process layer) infrastructure, but again will look to be the centralized utility for fintech and technology providers. Competition will remain intense, according to KPMG, especially for payments, settlements, core platforms, client onboarding, know your customer (KYC) etc.
The report emphasizes that there are regulatory challenges, since this model of banking does not fit or comply with much of the current regulatory requirements. This could be one of several roadblocks to advancement of the Invisible Bank concept.
For instance, in the platform layer component, there is the potential for systemic risk if the algorithms driving the decision-making process are wrong, resulting in wrong recommendations. To date, regulators have been reluctant to have a comfort level with the use of artificial intelligence.
In the product and process layers, there could be the integration of dozens of new entrants, some of whom may not be directly monitored by existing regulation. If traditional banking organizations provide these services within the Invisible Bank framework, who manages the regulatory risk?
Preparing to Become the Invisible Bank of the Future
The Invisible Bank is just one possible future of how banking’s transformational journey will play out, with voice assisted AI being one of the many opportunities that may result. According to Roemmele, “The first transition to this world for a bank is to present uniformly the exact taxonomy of services rendered and the exact benefits available. Once established, voice-assisted AI via personal digital assistants, will cull from ontologies to find perfect recommendations and financial solutions in real time.”
The technology required to build the Invisible Bank already exists today. Components such as APIs, cloud-based services, artificial intelligence and mass personalization are already becoming the foundation for the future at many financial institutions. But, in most cases, these technologies are being used in the peripheral systems rather than the core.
“A real shift in banking would require building out core platforms from scratch – and few banking CEOs have the risk appetite for that,” states KPMG. “The winners will be those that are able to utilize their data, drive down costs, build effective partnerships with a broad range of third parties, and of course, those with robust cyber security.”
Jim Marous is co-publisher of The Financial Brand and publisher of the Digital Banking Report, a subscription-based publication that provides deep insights into the digitization of banking, with over 150 reports in the digital archive available to subscribers. You can follow Jim on Twitter and LinkedIn, or visit his professional website.