As I mentioned recently, Easter announces that the annual spring gift giving season is truly upon us. This year, BIGinsight found in its latest consumer survey for NRF
that 82.3% of online consumers plan to celebrate Easter – a number that
has continued to inch up since 2007 (79.5%). Consumers intend to shop
across channels, with almost 9 out of 10 online Easter shoppers buying
food and candy, two-thirds expect to buy gifts, and approximately half
will be in the market for greeting cards and clothing, followed by
flowers and decorations. The combined net average forecast spend per
online consumer celebrating Easter this year is $150.70, a nice start to
Quarter 2.
So where should retailers focus their attention to capture the attention of online consumers?
Almost one in five (18.7%) of those consumers celebrating Easter will
be going online for some part of their Easter shopping this year, a
good leap even from last year
(14.8%). In line with online shopping trends, online consumers will be
spreading their Easter shopping activities over the web, across
smartphones and tablet devices and – the omnichannel shoppers that they
are – in traditional brick and mortar stores such as discount stores
(63.5%), department stores (42.6%), and specialty stores (25.4%).
Cross-channel marketing and promotions (such as promoting in-store
specials online and via mobile, matching in-store specials online,
offering access to customer ratings and reviews in the store, and so on)
will appeal to consumers who move quickly and effortlessly from one
customer touchpoint to the next.
Approximately half of online consumers who own a smartphone and/or
tablet device will be reaching for those as part of the shopping
process. Smartphone owners will use their device to research products
and compare prices (28.8%) and look up retailer information such as
location, store hours, etc. (22.3%). They will also use their smartphone
to redeem coupons (17%) and to purchase products (14.4%). It’s a great
opportunity to make sure your mobile-optimized site is working
seamlessly; that the retailer info is clear and easily accessible from
the first screen the consumer sees; and you are clearly communicating
your messages about Easter and spring offerings, both textually and
visually.
Similarly, over a third of online consumers who own tablet devices
will use those to research products and compare prices (38.4%), find
retailer information (28.4%), purchase products (27%) and redeem coupons
(18.9%). See how your tablet presence measures up – and where you can
fine tune – using the advice of Resource Interactive’s Stephen Burke who gave these primary tablet device design principles: make the tablet shopping experience engaging, share-able, shoppable, and extendable.
Tuesday, April 3, 2012
Extending the Experience Beyond the Device
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Over the last few years, the popularity of UX has grown by leaps and bounds. Companies have come to realize the importance of offering engaging experiences to their users, lest they risk losing them to competitors that have invested time and money into improving their product and service experiences.
An interesting side effect of this enhanced focus on UX is that it has helped make users more sophisticated. This, however, can be a double-edged sword; as users become more sophisticated their expectations also increase, and UX professionals must find new ways to meet these elevated expectations. One way to achieve this is to extend the experience beyond the device.
Most of the time when we think about UX, we are thinking within the confines of the digital world. What I'm suggesting, however, is that there are ways to extend the user's experience from the digital world into the real world. This is by no means an earth-shattering revelation; businesses have been working hard at offering exceptional offline experiences for decades. The explosion of the web and, more recently, mobile devices has given businesses an exciting channel to expand the experience.
This holistic approach can create very powerful experiences, which in turn can build tremendous brand loyalty. Imagine the enjoyment you get when using an application or a website that has a carefully crafted, wonderful experience. Now imagine you've just received the product you ordered via that app or site, and the same attention to detail has been paid to the presentation and experience of receiving and unboxing that item. How much more likely would you be to tell your friends about your experience? The next time you need that product or a similar one, where are you going to go?
Extending the experience can pay huge dividends in attracting and retaining customers, and some companies are already embracing this practice and providing inspiration for UX practitioners to use in their work.
In-Store Experience: Apple
It should come as no surprise that when talking about experience Apple jumps to the top of the list. For years, Apple has blazed the trail of UX with its hardware and software. So it made sense that when they opened their physical stores, that their focus on aesthetics and experience would continue. If you’ve ever been in an Apple store, you know what I mean—they're beautiful. It wasn't enough for Apple to simply have beautiful stores, though; they wanted shoppers to have a beautiful experience as well. They've done this in multiple ways, but perhaps the most interesting is their approach to the most dreaded of all shopping tasks: checking out.
When you walk into an Apple store, there’s an army of blue shirts there to assist you—nothing revolutionary here. But these folks are more than just your typical sales staff. They are armed with specially outfitted iPhones that can process transactions on the spot. Your blue shirt helps find the product, checks you out, and you’re out the door without ever waiting in line.
Suppose you just want to purchase some accessories for your iPad.
You don't really need to ask any questions, which is good because all
the blue shirts are busy anyway. Apple’s got you covered there, too.
Fire up the Apple Store app on your iDevice and use the new EasyPay
option. Just scan your product, pay with your iTunes account, and
leave—again, no waiting!
How does it apply?
Apple gets
it. Find the biggest pain points in a process and reduce or remove them.
As you are conducting your research, keep an eye out for processes,
bottlenecks, etc. that get in the way of users’ goals. After you’ve
identified these issues, develop innovative ways to reduce or eliminate
them. Try to find ways that you can empower your users to complete tasks
that they are currently unable to do on their own. One surefire way to
deliver a great experience to your users is to help make them more
efficient in their work.
Packaging and Delivery: Warby Parker
Buying eyeglasses can be a daunting task. You have to pick just the right frames to fit your face and match your style. This is nearly impossible to do by just looking at pictures of frames on a website.
Warby Parker realized this was a problem and came up with their Home Try-On Program. With this program, you select five frames from their site and they send them to you free of charge to try on at home. You’ve got five days to try on the different frames and solicit feedback from your family and friends. If they aren’t any help, you can upload pictures of yourself sporting the various frames to the Warby Parker Facebook page and they’ll help you choose the ones that look best. At the end of the five days, you simply ship the frames back using the included, prepaid shipping label. Didn’t find anything you like? Order five more.
This experience is great in that it solves the problem of trying to find the right frames online in a simple and elegant way. It also one-ups the traditional eyeglass store by giving you multiple options to take home and take your time to decide. No more pressure of being in the store, surrounded by hundreds of frames while trying to make an on-the-spot decision.
One of the things Warby Parker prides itself on is offering designer frames at low prices. The bargain prices don't mean they skimp on the experience, however. When your new frames arrive they come in an attractive package with a thank-you card. They also include a quality case and microfiber cleaning cloth at no additional charge. Warby Parker definitely sees the value in going the extra mile to deliver a memorable experience with their products. And their customers seem to have noticed; Warby Parker has experienced tremendous growth in the two years they've been operating, which goes to show that if you take the time to focus on the experience, you will be rewarded for it.
How does it apply?
Warby Parker took a difficult task that seemed almost impossible to do online, and made it not only possible via their website, but also enjoyable. If you’re working on a project that involves a process or task that people find difficult—especially in the real world—try to find ways not just to duplicate it with your app, but to also improve it and take some of the pain out of it. Leverage the benefits that technology can provide to create a better overall experience.The second thing we can learn from Warby Parker is that the experience shouldn’t end with the sale, and that surprising users by going that extra mile can be extremely powerful. Look for ways to provide value beyond what users expect. Maybe you can offer an in-store discount with the purchase of your app, or follow up with some swag mailed to people who sign up for your service. The opportunities are vast; be creative and be generous. It is likely that your investment will pay off.
Customer Service: Zappos
This final example is anecdotal, but I believe it is indicative of Zappos' approach to customer service as a whole. I was looking for some new shoes, so I thought I'd give Zappos a try. After a few minutes of searching, I couldn't find anything I was looking for. I took my frustrations to the Twitterverse lamenting how I couldn't find a thing on the new Zappos website. Shortly thereafter I received a reply from Zappos asking what I was looking for. We exchanged a few tweets and within an hour or so I was purchasing a new pair of shoes from their site. This was about three years ago and almost every pair of shoes I’ve purchased since has come from Zappos.Zappos’ shopping experience is nice, but it's nothing special. The thing that brings me back is that initial experience of the one-on-one assistance I received when I was having trouble. It can be hard to get that level of assistance from an employee in a brick-and-mortar store, let alone from someone thousands of miles away via a third-party web service.
Like the companies in the other examples, Zappos gets it. They understand the importance of creating a great experience for their customers and they are benefitting from it.
How does it apply?
This one is straightforward: deliver great customer service. Use all the tools at your disposal to deliver great customer service. Go out of your way to deliver great customer service. Companies live and die by their customers. Deliver great experiences by way of great customer service and you’re well on your way to success.There are many avenues for extending the experience beyond the device. From traditional venues like brick-and-mortar stores, to the virtual world of Twitter, there are a multitude of ways to deliver compelling experiences to users. Right now, extending the experience beyond the device is a good way to differentiate from the competition. As users continue to evolve, however, they will come to expect experiences to continue beyond the device. The companies that can realize this and deliver will succeed. Why not be on the cutting edge of that movement?
100 Things Every Designer Should Know About People
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This is the most helpful guide to user-interface design I've seen. It conveys what science knows about human behavior and how that should influence your design of a website or app. Why fight instincts? Here are 100 useable tips, explained, on taking advantage of the natural tendencies in the way our eyes, brains, and emotions work. Some of the 100 tips are common sense, and some are revelatory. Each is revealed with a principle, some examples, and a takeaway. I use this set as a kind of informal check-list of possibilities. As more of our life migrates to the web, it is ever more important to remember that design is about function, and not just good looks. This overlooked gem of a book encapsulates a lot of wisdom on how to make the functional work for people.
People believe that things shown close together belong together
*
People process information better in bite-sized chunks
Applying the concept of progressive disclosure:
Progressive disclosure means providing only the information people need at the moment.
Progressive disclosure requires multiple clicks. You may have heard it said that Web sites should minimize the number of times that people have to click to get detailed information. The number of clicks is not important. People are very willing to click multiple times. In fact, they won't even notice they're clicking if they're getting the right amount of information at each click to keep them going down the path. Think progressive disclosure; don't count clicks.
*
Steven Palmer (1981) traveled around the world and asked people to draw a coffee cup. Figure 5.2 shows examples of what they drew.
What most people drew when asked to draw a coffee cup
What's interesting about these drawings is the angle and perspective. A few of the cups are sketched straight on, but most are drawn from a perspective slightly above the cup looking down, and offset a little to the right or left. This has been dubbed the canonical perspective. Very few people would draw a coffee cup as in Figure 5.3, which is what you'd see if you were looking at a coffee cup from above.
Most people don't draw a coffee cup like this.
*
People read faster with a longer line strength, but they prefer a shorter line length
Have you ever had to decide what column width to use on a screen? Should it be a wide column with 100 characters per line? Or a short column with 50 characters per line? Or something in between?
The answer depends on whether you want people to read faster or to like the page.
Mary Dyson (2004) conducted research on line length, and combed other studies to determine what line length people prefer. Her work showed that 100 characters per line is the optimal length for on-screen reading speed; but we prefer a short or medium line length (45 to 72 characters per line).
*
Takeaways
Use concrete terms and icons. They will be easier to remember.
Let people rest (and even sleep) if you want them to remember information.
Try not to interrupt people if they are learning or encoding information.
Information in the middle of a presentation will be the least likely to be remembered.
*
People process information better in bite-sized chunks
Applying the concept of progressive disclosure:
Progressive disclosure means providing only the information people need at the moment.
Progressive disclosure requires multiple clicks. You may have heard it said that Web sites should minimize the number of times that people have to click to get detailed information. The number of clicks is not important. People are very willing to click multiple times. In fact, they won't even notice they're clicking if they're getting the right amount of information at each click to keep them going down the path. Think progressive disclosure; don't count clicks.
*
Steven Palmer (1981) traveled around the world and asked people to draw a coffee cup. Figure 5.2 shows examples of what they drew.
What most people drew when asked to draw a coffee cup
What's interesting about these drawings is the angle and perspective. A few of the cups are sketched straight on, but most are drawn from a perspective slightly above the cup looking down, and offset a little to the right or left. This has been dubbed the canonical perspective. Very few people would draw a coffee cup as in Figure 5.3, which is what you'd see if you were looking at a coffee cup from above.
Most people don't draw a coffee cup like this.
*
People read faster with a longer line strength, but they prefer a shorter line length
Have you ever had to decide what column width to use on a screen? Should it be a wide column with 100 characters per line? Or a short column with 50 characters per line? Or something in between?
The answer depends on whether you want people to read faster or to like the page.
Mary Dyson (2004) conducted research on line length, and combed other studies to determine what line length people prefer. Her work showed that 100 characters per line is the optimal length for on-screen reading speed; but we prefer a short or medium line length (45 to 72 characters per line).
*
Takeaways
Use concrete terms and icons. They will be easier to remember.
Let people rest (and even sleep) if you want them to remember information.
Try not to interrupt people if they are learning or encoding information.
Information in the middle of a presentation will be the least likely to be remembered.
Multi-Channel Attribution: Definitions, Models and a Reality Check
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April 2, 2012
A wise person said: "To guarantee success, spend 95% of your time defining the problem and 5% of the time solving it."I believe deeply in that quote. In my life I spend an extraordinary amount of time understanding the problem and attempting to define it clearly. As if by magic, I find that it is then much easier to find the optimal solution (or realize none exists!).
Multi-Channel Attribution is a red hot topic in our industry, and yet it is so poorly understood. I'm convinced that the resulting problems (confusion, FUD, angst, daily prayers, and wasted budget) are due to the lack of a clear framework that can help clearly define the problem.
In this post my hope is share a framework that will help define the problem clearly. Included in the post are recommendations for measurement and data analysis. And as if that was not enough, :), I'll close the post with my thoughts on digital marketing attribution models.
This is going to be a lot of fun. Roll up your sleeves, put a smile on your face, grab a pinch of common sense, a heavy dose of reality and let's go…
Three Types of Multi-Channel Attribution Problems.
A huge amount of confusion and disagreement on this topic exists simply because there is no general consensus about those three words. Multi-Channel Attribution.
So let's try and fix that problem.
There are three types of attribution problems in our non-line world.
Multi-Channel Attribution, Online to Store:
This is the attempt by Marketers and Analysts to try and understand the offline impact (revenue/brand value/butts in seats/phone calls/etc) driven by online marketing and advertising. We'll refer to this quest for doing effective attribution as MCA-O2S.
While I'm using the term Store here, it encompasses sales (or leads or catalog requests) driven to a retail store or company call center, people driven to donate blood via online campaigns, or essentially any offline outcome driven by the online channel.
An example of MCA-O2S is Verizon wanting to know how many in-store offline phone activations are driven by online search advertising, for every online activation that the same search advertising drives.
[In case you were curious... It's 5 new accounts activated offline for every 1 activated online! If you are not calculating the offline impact, and you are not giving your online channel due credit. In this case, it would be 5x less credit! You can see why MCA-O2S is supremely critical for every company on the planet.]
Here's the Post-It on which I'd sketched MCA-O2S in planning this post. The red dots represent activity we would like to ensure we are measuring to 1) ensure we understand behavior, and 2) deliver insights that will influence our marketing and advertising…
So when you meet a CEO and they use say "Help me solve the amazing multi-channel attribution problem", you say: "which type of MCA are you interested in?" Clarity will help foster a valuable conversation.
Almost all current, hot and heavy, literature on the topic of attribution modeling does not cover MCA-O2S. That's because when it comes to MCA-O2S your only bffs are a set of 16 strategies I've outlined over two posts (links immediately below) or the fantastic world of controlled experiments (as in the Verizon case above). So less automated algorithms "distributing credit" and more thoughtful deliberative discreet measurement strategies that inform strategic decisions.
Two helpful blog posts on multi-channel analytics: 1. Tracking online impact of offline advertising. 2. Tracking offline impact of online advertising.
MCA-O2S. It's mandatory. Attribution is driven by experiments. And when you win, you win huge!
Multi-Channel Attribution, Across Multiple Screens:
Senior leaders, especially in larger companies, have started to refer to this when they use the magical words multi-channel attribution.
With the massive adoption of mobile phones and tablets we are all increasingly "four screen" people (TV, desktop, tablets, smart phones). That has directly translated into a more complex fragmented influence landscape (drives the "old timers" bananas). That in turn has translated into many senior leaders deeply desiring, as they put it, "multi-channel attribution." What they really mean is MCA-AMS.
What they really really want is to understand how individuals experience a company or government's digital existence across multiple devices, what media (advertising and marketing) they are being exposed to, and what outcomes (conversions!) are happening as a result.
An example of MCA-AMS is the ability to understand that a search I did on my tablet computer while watching a television commercial resulted in a click on a paid search ad to a camera site which logged into my memory which later caused me to read reviews of the camera on my Nexus S while stuck in traffic and that finally caused a sale for Sony when I got home and happened to be on my laptop.
Attribution in this case is the quest to apportion credit across the TV commercial, tablet paid search ad, reviews read on on the mobile phone for a "direct" conversion on the PC. Amazing, right?
Here's my sketch on MCA-AMS and the raw complexity of the customer experience that we are trying to understand… the red dots indicate what we're trying to measure and understand the impact of…
Perhaps the only exceptions to the "its almost impossible" scenario would be companies that service customers who are mostly logged in (think Amazon, NY Times) across all four screens all the time. Such companies usually also own massive data warehouses where they have an ability to periodically do cannonballs into the data and identify correlations in consumption and purchase patterns. Often, though not always, they can also tease out causations between devices used during outcomes (five-second segmentation in say Google Analytics) and their media plans while focusing on customer analysis (not visitors, not cookies, not uuids, customers).
Even then it is hard, very hard. And for the rest of us this will remain a complex, and I'm sorry to be so real, unsolvable challenge. At least for now.
Some ideas from the two multi-channel blog posts above can help with MCA-AMS. I've leveraged controlled experiments to get very good "kinda sorta understanding" of reality.
I believe that real solutions will come from the evolution of cookies, updating privacy policies, government decisions and evolving user habits. All that first, then our ability to have nonline data.
Because of all of the above you can see why attribution models don't even enter the picture with MCA-AMS. But when you meet executives and they say "help us with our multi-channel attribution problem", most definitely ask the clarifying question: "do you mean MCA-O2S or MCA-AMS?"
MCA-AMS. Complex, hard challenge. Not a huge problem yet for most, but heading in that direction.
Multi-Channel Attribution, Across Digital Channels:
Almost all of the time when people in our ecosystem (unlike CEOs, CMOs) talk about Multi-Channel Attribution, this is the one they are referring to.
MCA-ADC is the effort to understand which digital marketing channels (Social, Display, YouTube, Referral, Email, Search, others) contributed to a particular conversion (or multiple conversions).
At the moment all web analytics tools, like SiteCatalyst, WebTrends, Google Analytics, CoreMetrics, and others, by default attribute a conversion to the channel immediately prior to the conversion. This is also known as last click attribution.
With MCA-ADC you are trying to go beyond the last click and get this, complete, picture of all marketing activity prior to the conversion (in this case from Google Analytics):
For this website, 767 conversions came from people who visited the site in the above precise order starting with social then a direct visit then an organic search then a referral click-through and finally one last direct visit which lead to the conversions.
The attribution bit here is the burning desire inside all digital marketers to figure out how to dole out credit for the above conversions. Should Direct get 50%? How about Social? 100%? What about Organic? 2%? But let's put that delightful thought on the back burner for just a minute while we understand a critical, often hidden, nuance. [Analysis Ninjas are magnificent at understanding nuance!]
When people talk about MCA-ADC they are still just talking about one device. Because in very close to 0% of the cases do any of these analytics tool have an idea about the behavior of one homo sapien across multiple screens (AMS).
So what you are seeing above are all the conversions that can be tied to multiple visits by a unique browser (notice I did not say person) to your website/digital existence. BTW it is fantastic that GA does this because most other tools don't even show you this.
Say, the Organic Search above had happened on a mobile phone… regardless of the digital analytics tool used, to most websites today that visit would be invisible in the above chain (cookies!). #omg
Hence it is important to separate out MCA-AMS (across multiple screens) from MCA-ADC (across digital channels) – at least for now, until the cookies, ids, privacy policies, government guidance and user habits problem is solved.
When it comes to measuring MCA-AMS you'll use the guidance provided in the above section. For MCA-ADC you'll use a different set of reports (multi-channel funnels ) and attribution models.
I'm sure you are already familiar with nuance number two when it comes to MCA-ADC. A blind-spot if you will.
The above picture does not capture what the impact of this behavior was on your offline existence (O2S). Web Analytics tools are not awesome at that. Ok, they stink at it.
So it is possible that an additional 3,835 people went and made purchases in your stores or via your phone channel (taking the Verizon numbers from above). That would also be invisible from the above report. None of the channels above, whether glorious social, beloved direct, magnificent search, sweet referral, would ever get "credit." Unless you are willing to use the methodologies outlined in the MCA-O2S section above.
When you talk about MCA-ADC, ensure that you are aware and communicate to your leadership, that you are not reporting on MCA-O2S (online to store) and it is extremely unlikely to be reporting the impact of MCA-AMS.
Here's one last Post-It sketch. The red dots are what you are likely measuring when you attempt MCA-ADC…
Now it is true that with sufficient analytical skills, time, patience, and God's direct blessing to you, it might be possible to do complete multi-channel attribution analysis where the multi-channel includes multiple online ad channels, behavior of the person across devices and the impact online and offline.
Sadly, that is incredibly hard to do as a whole. And when I say incredibly hard, I mean almost impossible. And when I say almost impossible, I mean only attempt that after you know you've fixed all other problems with your advertising, your online and offline existence and your people. All three.
I know that sounds like a bummer, but a dose of reality is particularly needed in this discussion. There are simply too many fake promises being made by vendors, consultants, tweeters, gurus and fairies. That is unhelpful to the entire ecosystem.
To close this section…
Next time you hear someone utter the words multi-channel attribution, the single greatest gift you can give yourself is to ask in your sweetest possible voice: "Are you referring to MCA-O2S, MCA-AMS or MCA-ADC?"
You'll earn their respect for knowing that there are three types, and you'll be able to put into context what they are asking for and proceed to have a career and business-enhancing discussion.
Multi-Channel Attribution Models.
For MCA-O2S and MCA-AMS, it is a complex undertaking to identify "which advertising/marketing vehicle deserves how much credit." It requires patience and skills. And it requires your execution of multiple of the 16 strategies I've outlined for tracking online impact of offline and offline impact of online. Even more, it requires an ability (people + skills + desire) to execute controlled experiments.
So the question "who deserves how much credit" is tertiary at best.
With MCA-ADC that quest is a little bit easier. We have the multi-channel funnel reports at our disposal. Additionally in some tools we also have an ability to apply attribution models to the behavior you see in the two pictures above in the MCA-ADC section. #sweetness
The most common attribution models bundled into even the simplest web analytics tools are: Last click, first click, and even distribution.
If you are lucky, you have access to a more sophisticated tool which would include: Adjustable, based on mathematical algorithms, time decay model.
If you are among the chosen few, you'll likely have access to a digital analytics tool that allows you to create a customized attribution model.
Each of these models are applied to MCA-ADC (still without benefit of O2C or AMS) and provide you with incrementally better understanding of your digital media spend.
Each of these models comes with its own pros and cons. [If you have my book Web Analytics 2.0 please jump to page 358.] Some of them have more cons and barely any pros. Those should be avoided like the plague.
A couple of them pass the common sense test, and hence will put you in a better place than staying with last click attribution.
But most of what you'll get out of playing with these models is a deep and profound appreciation for how they'll, even in their most shining moment, give you directional guidance how to adjust your media spend (shift dollars/euros/pesos from Search to Display or from Display to Email or… other combinations).
You'll realize (even if you use the greatest customized model created by your most magnificent consultant at a equally magnificent cost to you) that success then will come not from that rough output, but rather from your ability to take that rough output, make changes, observe the impact (over weeks, or months if you are small sized), identify insights and be less wrong over time.
If you happen to be in a larger company, say you spend more than $10 million on digital marketing per year, you'll quickly see, having learned to be less wrong over time, that the question you want to answer with multi-channel attribution modeling is not "who gets how much credit" but rather "how can I optimally balance my digital marketing portfolio."
That will then drive you to seek solace in the arms of the only solution that actually works. The solution that is hard. The solution that requires unique people skills and an undying desire to scale un-imagined heights of glory. Media Mix Models. Executed via persistent controlled experiments.
When you reach that point, fame, fortune and happiness will be yours.
This is a tough challenge. Simply because reality is complicated.
Customer experiences are ever more complex, influence channels intersect a lot more, content consumption is fragmented, the three-step "attract, acquire, retain" model is now broken into 37 different pieces.
So, you don't have a choice. You are going to have to deal with the multi-channel attribution problems, all three of them, if you want your company to have an effective advertising and marketing strategy.
Here's the good news: You don't have to try to boil the ocean in one go. In fact, that might be hazardous to your health if you attempt to do that. Take gradual steps. Increase your sophistication over time.
Here's what I recommend:
-
1. First clarify what problem you are solving for your management team. O2S or AMS or ADC.
2. Use the appropriate set of solution (see sections above). If MCA-ADC…
3. Get really, really good at understanding your multi-channel funnel reports. They are free. They are awesome. Use the Venn diagram in the Overview report to display reality to your management team. They'll love you, and stop wasting money.
4. Start to experiment with the simple models. You are moving away from last click, you'll abandon first and even very quickly. Spend some love and attention on the time decay attribution model (ideally with several mathematical options to apply).
5. Experiment with changes in your digital portfolio based on your time decay results.
6. Measure outcomes. Go back. Analyze the data. Change some more.
7. As you master that, shift slowly to playing with media mix modeling type controlled experiments.
If you understand the frameworks, if you internalize the challenges, if you define your company's immediate unique problem clearly, and follow a step wise approach outline above you'll not just do fine. You'll be fantastic.
Good luck!
Monday, April 2, 2012
Marketing To Women: 30 Stats To Know
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by Ekaterina Walter,
Mar 28, 2012, 7:48 AM
Women are earning, spending, and
influencing spending at a greater rate than ever before -- and they
account for $7 trillion in consumer and business spending in the United
States, and over the
next decade they will control two-thirds of consumer wealth. Women make
or influence 85 percent of all purchasing decisions, and purchase over
50 percent of traditional male products, including
automobiles, home improvement products and consumer electronics.
But 91% of women say that advertisers don't understand them.
Recognizing the power and influence of women must be a top priority for marketers if they are going to tap into the market's full potential. Here are 30 surprising stats to help marketers get a handle on this misunderstood demographic.
Earning Power
1. The average American woman is expected to earn more than the average American male by 2028
2. Fifty-one percent of U.S. private wealth is controlled by women
3. Women account for over 50% of all stock ownership in the U.S.
4. Women control more than 60% of all personal wealth in the U.S.
Spending Power
1. Women account for 85% of all consumer purchases, including everything from autos to health care
2. Women make 80% of healthcare decisions and 68 percent of new car purchase decisions
3. Seventy-five percent of women identified themselves as the primary shoppers for their households
4. Women influenced $90 billion of consumer electronic purchases in 2007
5. Nearly 50% of women say they want more green choices, with 37% are more likely to pay attention to brands that are committed to environmental causes
Women and Cars
1. Women buy more than half of the new cars in the U.S., and influence up to 80% of all car purchases
2. Women request 65% of the service work done at dealerships
3. Women spend over $200 billion on new cars and mechanical servicing of vehicles each year
4. Forty-five percent of all light trucks and SUVs are purchased by women
Mom Power
1. Moms represent a $2.4 trillion market
2. Fifty-five percent of active (daily) social media moms said they made their purchase because of a recommendation from a personal review blog
3. 18.3 million Internet users who are moms read blogs at least once a month
4. In 2014, 63% (nearly 21 million) of all online moms will read blogs
5. Moms mention brands an average of 73 times per week compared with just 57 times per week among males
6. Seventy-seven percent of mom bloggers will only write about products or brands whose reputations they approve of, and another 14% will write about brands or products they boycott
7. Ninety percent of moms are online vs. just 76% of women in general
8. Sixty-four percent of moms ask other mothers for advice before they purchase a new product and 63% of all mothers surveyed consider other moms the most credible experts when they have questions
Women Online
1. As early as 2000, women were found to have surpassed men in Internet usage
2. Seventy-eight percent of women in the U.S. use the Internet for product information before making a purchase
3. Thirty-three percent research products and services online before buying offline
4. Women account for 58% of all total online spending
5. Twenty-two percent shop online at least once a day
6. Ninety-two percent pass along information about deals or finds to others
7. The average number of contacts in their e-mail or mobile lists is 171
8. Seventy-six percent want to be part of a special or select panel
9. Fifty-eight percent would toss a TV if they had to get rid of one digital device (only 11% would ditch their laptops)
The sources for the statistics cited in this article are as follows: She-Economy, Ms Smith Marketing, StartUpNation, Clickz, Inc.com, Girl Power Marketing, Catalyst, Forbes.
But 91% of women say that advertisers don't understand them.
Recognizing the power and influence of women must be a top priority for marketers if they are going to tap into the market's full potential. Here are 30 surprising stats to help marketers get a handle on this misunderstood demographic.
Earning Power
1. The average American woman is expected to earn more than the average American male by 2028
2. Fifty-one percent of U.S. private wealth is controlled by women
3. Women account for over 50% of all stock ownership in the U.S.
4. Women control more than 60% of all personal wealth in the U.S.
Spending Power
1. Women account for 85% of all consumer purchases, including everything from autos to health care
2. Women make 80% of healthcare decisions and 68 percent of new car purchase decisions
3. Seventy-five percent of women identified themselves as the primary shoppers for their households
4. Women influenced $90 billion of consumer electronic purchases in 2007
5. Nearly 50% of women say they want more green choices, with 37% are more likely to pay attention to brands that are committed to environmental causes
Women and Cars
1. Women buy more than half of the new cars in the U.S., and influence up to 80% of all car purchases
2. Women request 65% of the service work done at dealerships
3. Women spend over $200 billion on new cars and mechanical servicing of vehicles each year
4. Forty-five percent of all light trucks and SUVs are purchased by women
Mom Power
1. Moms represent a $2.4 trillion market
2. Fifty-five percent of active (daily) social media moms said they made their purchase because of a recommendation from a personal review blog
3. 18.3 million Internet users who are moms read blogs at least once a month
4. In 2014, 63% (nearly 21 million) of all online moms will read blogs
5. Moms mention brands an average of 73 times per week compared with just 57 times per week among males
6. Seventy-seven percent of mom bloggers will only write about products or brands whose reputations they approve of, and another 14% will write about brands or products they boycott
7. Ninety percent of moms are online vs. just 76% of women in general
8. Sixty-four percent of moms ask other mothers for advice before they purchase a new product and 63% of all mothers surveyed consider other moms the most credible experts when they have questions
Women Online
1. As early as 2000, women were found to have surpassed men in Internet usage
2. Seventy-eight percent of women in the U.S. use the Internet for product information before making a purchase
3. Thirty-three percent research products and services online before buying offline
4. Women account for 58% of all total online spending
5. Twenty-two percent shop online at least once a day
6. Ninety-two percent pass along information about deals or finds to others
7. The average number of contacts in their e-mail or mobile lists is 171
8. Seventy-six percent want to be part of a special or select panel
9. Fifty-eight percent would toss a TV if they had to get rid of one digital device (only 11% would ditch their laptops)
The sources for the statistics cited in this article are as follows: She-Economy, Ms Smith Marketing, StartUpNation, Clickz, Inc.com, Girl Power Marketing, Catalyst, Forbes.
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