How to Stop Annoying Your Customers Summit in San Francisco, CA

Conclusions Paper
How to Stop Annoying Your Customers
Insights from a presentation at the eMetrics Marketing Optimization
Summit in San Francisco, CA
Featuring:
Peter Kear, Vice President of Sales and Marketing, IS Solutions PLC
Retha Keyser, Business Development Manager, SAS Customer
Intelligence Global Practice
How to Stop Annoying Your Customers
Customer relationships are like personal relationships – what you put in is what you
get out. You both have a role to play, and in the case of a company, it’s important to
make extra efforts to show you care about and value your customers.
But many companies stick to routines ... create monotony ... and continuously
confuse and annoy their customers. By failing to plan and operate in sync, individual
departments vie for a customer’s attention and reveal the company’s lack of
understanding of that customer.
Fortunately, customer analytics enable a new and better approach.
That was the topic of a SAS-sponsored presentation at the eMetrics Marketing
Optimization Summit in San Francisco. Retha Keyser, Business Development
Manager for the SAS Customer Intelligence Global Practice, talked about
technologies that help solve the complex challenges of high-velocity, multichannel
marketing. Peter Kear, Vice President of Sales and Marketing for IS Solutions, a
leader in online managed services, provided real-world examples of the results
seen when these technologies are put into action.
The Quest for Customer Loyalty
In simpler times, companies earned customer loyalty on the basis of personal
interactions. “You went to the store; the shopkeeper knew you and dealt with you
on a one-to-one basis,” said Keyser. “With the rise of mass marketing and mass
media, we lost touch with the customer. Companies blasted out campaigns via
mass media, and they weren’t sure who they were hitting.”
In the desire to recapture a one-to-one type of relationship, organizations put
in automated systems to target customers and manage campaigns. The idea
was to acquire the most desirable customer segments from purchased lists by
contacting them through direct mail, email, telesales, the sales force, catalogs
and other direct channels.
“The problem is that this activity often focused on acquisition – growing the customer
base and the number of products held,” said Keyser. “It wasn’t always focused on
growing loyalty. As a result, a lot of money was spent, but you weren’t always sure
what the returns were.”
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How to Stop Annoying Your Customers
Does the right hand know what the left is doing?
Coordinate promotional efforts across product lines and brands.
All too often, business units within an organization promote their brands and products
with tunnel vision, bombarding customers with conflicting and irrelevant contacts. It’s
a costly waste of money that undermines customer goodwill – yet it’s a surprisingly
common scenario.
The online retailer has multiple brands that sell similar products targeted for
similar customer segments. The company’s websites generate 50 to 55 million
Web sessions a month – a daunting amount of data to correlate. So instead, the
company simply generated random promotions across all their brands – tens of
thousands of promotions a month.
The result? Massive levels of unsubscribes.
“They were just bombarding their customers the whole time,” said Kear of this IS
Solutions client. “It was very confusing, and it annoyed customers. So we created
a single customer view that integrates all of their Web session history across brands.
Now we could start to understand more about customers, what they’re doing, what
they’ve done in the past and across Web domains. This enabled the retailer to track
customers as they visited each of those domains on each of those websites.
The result? “We stopped annoying the customer, which was the key issue,” said Kear.
“Cross-domain tracking really improved cross- and up-sell, and enabled personalized
offers across multiple channels. This generated $10 million of additional revenue in the
first year alone.”
Are you flooding good customers with irrelevant offers?
Correlate Web data with back-office history and call center activity.
Companies have more opportunities than ever to gain information about customers
(good), but if you don’t make use of it all to generate meaningful customer intelligence
(bad), you just end up with more opportunities to bug them with the wrong offers –
or simply too many offers.
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How to Stop Annoying Your Customers
Email opt-in campaigns, Web tracking, social media monitoring, online forms,
mobile devices … the explosion of online channels provides a wellspring of
marketing data, said Keyser. “Think about a retailer, for example. In the real world,
you walk down the aisle. You pick up a tin of beans. You put it down. You pick up
the next one. You put it down. The retailer doesn’t see that. On the Web, you see
every one of those interactions.”
But what are companies doing with all that information? Typically, those various
digital channels are being managed in a siloed fashion, said Keyser. “As a result,
people get inundated with multiple offers from multiple channels – not just in
marketing, but in sales and service as well, where call center contacts are seen
as cross-sell opportunities. There’s no cohesion, no controlled effort. As a result,
customers receive too much information, and there’s a lot of customer fatigue.
“This problem is intensifying because of the velocity and real-time nature of Web
and mobile applications,” said Keyser. “Customers are getting more noise and more
irrelevant material all the time – and they are overwhelmed. They are saying, ‘I receive
too much advertising. I receive too many emails.’ And eventually what do you do?
You opt out. You put yourself on Do Not Call lists. You just say, ‘I don’t want this
anymore. I have too much to deal with.’”
■“Customers are getting more noise
and more irrelevant material all the
time, and it’s too much. They can’t
deal with it, and they won’t look at
anything that you’re sending them
any longer. Customers are just giving up.”
Retha Keyser, Business Development
Manager, SAS Customer Intelligence
Global Practice
A multinational, multichannel bank interacts with its customers on a one-to-one
basis via branch offices, call centers and the Web. There were huge quantities of
back-office data on customer history, but surprisingly little overall knowledge of
any given customer’s relationship with the bank across channels.
As a result, the bank didn’t really know which customers were its most valuable
ones and what those customers might value most. The bank’s promotions were
good offers but not necessarily relevant to recipients. Customers were ignoring the
promotions and tuning out.
“For this client, we implemented a multichannel data warehouse that enabled a single
customer view,” said Kear, “but this time we expanded it to include not only data
gathered from the Web and customer history, but also from the call center. Combining
that information, we could now really understand the highest-valued customers
and what those customers were looking for. The bank could then create relevant,
multichannel campaigns based on true knowledge of the customer’s activities across
all those points of contact.”
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How to Stop Annoying Your Customers
This unified perspective enabled the bank to market far more effectively to highvalue customers who had previously been underserved – customers who are
worth 25 percent more to the institution than its run-of-the-mill customers.
There are petabytes of clues out there, but are they being used?
Automatically incorporate customer insight into action.
“In every single channel you collect data about customer attributes and activities,”
said Keyser. “When you combine that information, you can start to understand a
pattern as a sequence of behaviors across channels, and that’s a very different level
of insight.” For example:
• Customer No. 1 comes to your website from a social network, looks at particular
products, returns three times to look at the technical aspects of a product, phones
the call center with questions and then walks into the store to buy something.
• Customer No. 2 searches for your product on Google, visits your website
to configure a feature-rich product, then slowly but surely eliminates features
to get to a lower price point, and when the shipping comes up, abandons the
shopping cart.
The purchase process is no longer just a point in time or a single interaction. Today,
your promotional decisions should be made in that full context. If you know that
context, you might choose to offer Customer No. 2 a 10 percent discount or a
waiver of the shipping fee, because you know he is a regular customer and recently
purchased a very high-value item from you.
“That’s the kind of information that we are now being able to collect and then draw
intelligence from to give back to people to take much better actions,” said Keyser.
But even when full context is available – with the potential for a more complete
understanding of the customer – is that knowledge being translated into action?
The online comparison shopping site offers 15 channels that address different
consumer needs, such as travel, insurance and mortgages. For instance, a
customer could use the company’s website to compare airfares from different
airlines or mortgages from different lenders, and make a purchase decision.
Trouble was, the company took a scattergun approach to marketing across
its many channels. It generated thousands of promotions a month with no
targeting at all. The company wanted to increase sales per customer, but with
petabytes of data to sift through from 15 domains, how could it know where
to start?
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■ “If you give customers too much
information that lacks relevance,
they just tune out.”
Peter Kear, VP Sales and Marketing,
IS Solutions PLC
How to Stop Annoying Your Customers
“For this client, we created a single customer view in a data warehouse that
integrated Web history across channels and automated their inbound and outbound
campaigns,” said Kear. “The company could now make more relevant cross-sell and
up-sell offers based on the customer’s interest, behavior and propensity to buy.
“The company’s goal was to try to increase the previous average sale of 1.2 products
per customer to 1.4 to 1.5. They actually achieved 1.5 products per customer, which
meant a 10 percent increase in net profit. To these guys, this is a huge return on
investment in an incredibly short period of time.”
‘I Want It, and I Might Want It Now – If You Tell Me What It Is.’
Marketing moves from batch to real time.
“Traditional campaigns were mostly batch-oriented,” Keyser recalled. “On a nightly
basis, your campaign tool would select what goes out the door for emails, mail,
telesales and leads for your sales force. The velocity of communication in digital
channels has redefined the expectations. Customers now expect you to respond
much faster, so when they come back to you this afternoon or tomorrow, don’t
offer them the same thing you did yesterday or this morning.” The world is just not
that static anymore.
“We’re seeing a paradigm shift from pre-scoring customers overnight in your data
warehouse for campaign selection, to real-time scoring within the current session,
using in-session and historical data to make a new offer on the fly at the individual
customer level.”
A multinational insurance company that offered multiple products experienced
very high customer churn because its pricing was out of touch with the market.
When policies came up for renewal, customers visited price comparison
websites where they could easily compare rates.
Many of them opted for a lower-priced insurer, even though the new insurer
might not serve their needs as well. But how would the customer know? Rate
was the most obvious decision factor – and usually the only one.
“We worked with this company to create a single customer view that combined all of
the customers’ interactions and history, coupled with real-time decisioning,” said Kear.
“We’re linking into the underwriting systems to make sure we can offer the right level
of premiums at the right times – so offers to customers become more relevant and
are delivered via the customer’s preferred channel. “The result has been an 8 percent
reduction in customer churn, representing a significant amount of dollars.”
A Pan-European holiday retailer was having trouble understanding
its customers because it operated in disconnected online and offline
environments: retail outlets, the Web and call center. The only customer history
the company had was locked away in back-office systems.
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How to Stop Annoying Your Customers
The best Marketing could do was to offer untargeted campaigns. A customer
hoping to vacation in the Seychelles might get offers for flights to Europe – or
vice versa. The result, not too surprising, was a huge volume of unsubscribes.
“For this client, we implemented a single customer view with real-time decisioning
and personalization across all channels, including the actual stores,” said Kear. “So
if you’re a customer walking into one of the travel stores, we know a little bit about
you and what you’ve done in the past. The in-store agent has that information and
can discuss holiday options relevant to that customer – and offer discounts based
on that known history,” not just random discounts across the board.
Within 12 months, the company reduced the level of unsubscribes by 11 percent
and increased the conversion rate by some 6 percent – significant gains from simply
making better use of the customer data they already had.
With real-time decision management, answers are available on demand, said Keyser.
“We can collect Web data in real time, combine it with offline data and do predictive
scoring in real time – then parse the result back to the Web page in real time.” You can
then make an offer based not just on A/B testing but on up-to-the-minute knowledge
of the customer’s interests as expressed in online activity.
For instance, if the customer is browsing laptops on your website, you might put forth
a laptop offer – but when the customer starts looking at printers, you’d better switch
gears and spotlight printers – not just any printers, but the models that are compatible
with the desktop computer the customer purchased from you last month.
This ideal is reality with real-time decision management.
What’s that online customer doing in your store?
Deliver real-time intelligence that correlates customer behaviors
online and in-store.
For all the sophistication of e-commerce, there are still some major disconnects, said
Keyser. Few organizations effectively link online activity with activity in brick-and-mortar
stores. That disconnect between the real world and the Web can be just as annoying
to customers as a disconnect between product lines/brands within a single channel.
Keyser described a typical example: “Somebody comes to the website, puts something
in the shopping cart, and then abandons the shopping cart. The company immediately
sends out an email to offer that customer an enticement on the abandoned product,
perhaps a discount or an offer to waive the shipping costs. Well guess what? By the time
the email is generated and received, the guy has already walked into a store and bought
the product, but the company was unaware of that, because there was no integration.
So it is very important to have that data integration and real-time conversation.”
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■ Within 12 months, the company
reduced the level of unsubscribes
by 11 percent and increased the
conversion rate by some 6 percent –
significant gains from simply making
better use of the customer data they
already had.
How to Stop Annoying Your Customers
“We have to include all the conversations that we’re having with the customer across
the organization and then make that intelligence available back to the touch points.
Analytics enables the company to act on intelligent decisions right at the point of
customer contact, not just back in the head office.”
Are you overlooking a goldmine of new knowledge?
Learn more about customers from what they say, not just what they do.
By some estimates, structured (numerical) data – such as the data in point-ofsale systems and back-office systems – represents only about 25 percent of
the information in an organization. A minimum of 70 percent of data is actually
unstructured data – freeform text, images, audio and video captured from online
and offline sources.
■ “We have to include all the
Unstructured data comes from Web documents, emails, contact center records,
social media, blogs, claims, customer complaints and any number of other sources.
The remaining 5 percent or so of an organization’s information is considered
semistructured – a hybrid of freeform and structured data – such as an email, which
has structured data in the header and unstructured text in the body.
conversations that we’re having with
This data volume is expected to expand by 35 to 45 percent in the coming years
as social media becomes even more widely used for commerce.
on intelligent decisions right at the
“Social media is a great source of acquiring new customers at a very, very low cost,”
said Keyser. “As we see the cost per thousand impressions dropping – both on the
banner ads as well as on the rich media side – we will see budgets shifting more
towards new media, which will bring more traffic, more data and more interactions
coming from these channels.”
the customer across the organization
and then make that intelligence
available back to the touch points.
Analytics enables the company to act
point of customer contact, not just
back in the head office.”
Retha Keyser, Business Development
Manager, SAS Customer Intelligence
Global Practice
There’s a dark side to this boon in low-cost public relations. Customer complaints
– which were once hidden in a company’s email archives that no one ever read
or responded to – are now open for public display and comment on review sites,
Facebook pages and blogs. Organizations cannot afford to ignore the implications.
You are being talked about; you might as well join the conversation or at least learn
from it.
This is where text analytics come in. Text analytics extract relevant information and
interpret, mine and structure that information to reveal patterns, sentiments and
relationships within and among documents.
Text analytics help answer some interesting questions, said Keyser: “What are the
words that customers are using around a particular topic? Is it a positive or negative
sentiment? How is that positively or negatively affecting your brand? But more
important, is it driving traffic to your website or away from it? How is it affecting the
quality of customer engagements, the number of sales and the RFM scores? Which
customers have the most influence, positively and negatively, in driving interactions to
your other channels?”
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How to Stop Annoying Your Customers
Text analytics answer these questions, and not only for online communications.
“The same taxonomy that we use for the social media channel we can apply
to any text data,” said Keyser. “Using text mining, we can analyze all types of
communications that the customer is having with us.”
Annoyance-Free Marketing – How to Get Started
“To have happy customers – to not irritate and annoy customers – you have to
automate your marketing,” said Keyser, who outlined the key steps to developing
a “learning organization”:
1. Collect as much of the right data as possible. “Start with the transactions
and the channel systems, and collect as much information as you possibly can,”
said Keyser. Make sure you are collecting the right information at the right level
of detail. For example, you cannot predict the sale of ice cream very accurately
if you don’t collect the daily temperature, and you can’t do meaningful analysis
at the individual customer level if all you have from Web and mobile channels is
summary-level reports.
2. Create a 360-degree customer view that includes data from every relevant
source possible – from back-office systems to online and offline customer
contact channels for every business unit, product or brand.
“You need to include that channel behavior, because that is a very important
source of behavioral data that gives you great levels of accuracy that you
wouldn’t have with just pure demographic data,” said Keyser. Good data
management tools and common metadata make it possible to incorporate
data from disparate and incompatible source systems.
3. Build customer intelligence on top of the data warehouse, said Keyser.
“Without analytics, it is impossible to build rules with the necessary level of
specificity, such as ‘This campaign should go out to people who have brown
eyes or blue eyes and came to the website from Google and then did this and
then did not do this and so on.’”
4. Automate inbound and outbound communications. “When we move to real
time, and the customer has opted out, your only chance is to catch them while
they’re coming to you,” said Keyser. “You need to know the right offer to make
while they talking to your call center agents, while they’re walking into your
store, or while they are navigating your website.” That responsiveness requires
automation with real-time decision management.
5. Add scope and analytic sophistication as you go. “Continuously keep on
building, because as we’ve seen over the past five or 10 years, new channels
are constantly emerging,” said Keyser.
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How to Stop Annoying Your Customers
Add predictive analytics to segment customers on a much more dynamic basis, to
automatically detect what drives different groups of behaviors and outcomes. Use text
mining to understand unstructured data. Add constraint-based optimization to make
the best choices within known limits set by contact policies and internal resources.
6. Make analytic insights available at customer touch points across marketing,
sales and service. “We’re seeing disconnects happening where the service side
is not aware of what’s happening on the sales side, and vice versa,” said Keyser.
“You have to optimize all those interactions, inbound and outbound, with all your
brands, products and across all the different channels. This is not simple to do,
but the technology is there to enable it.”
Closing Thoughts
In a multichannel digital world, customer stories are told on your website, on the
phone with your call center, in person, and on social media.
Customer analytics enable leading organizations to stay in touch with, and respond
to, these stories. By aligning and timing the content and means of communicating
with your customers in an effective way, you show that you’re listening, hearing and
understanding what your customers want.
Ultimately, the organization ends up building an institutional memory of a customer,
which is essential, said Keyser. “Suppose I have a relationship with you, and you
have to tell me everything about you every single time I talk with you; I just forget
everything that we’ve done in the past. We’re not going to have a very good
relationship, and it is definitely not going to develop into a friendship. The same
thing is happening in the organization.”
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