Optimization
Embrace the change
- By Amy MANUS | Strategy April 18th, 2013
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While KPIs, measurement models, attribution, and optimization remain go-to frameworks of digital marketing plans, I often get the feeling we’re leaning too much on these performance metrics and not actually taking a step back and looking at the bigger picture. Instead of asking how we can decrease the CPA by 10 percent or increase enrollments by changing frequency caps, we need to do our due diligence to expand beyond our silos and look at the big picture to understand how evolving consumer consumption and usage is truly impacting our business.
U.S. Internet usage has reached saturation, and with that, so has usage of search engines and email. According to eMarketer, overall Internet penetration came in between 75 and 85 percent (depending on the source) in 2012 with a projected 2.4 percent increase this year. With saturation, consumers are developing a more cultured palate for their online experiences, and their expectations have evolved to determine what is and is not acceptable. The days of championing the glorious measureable results of digital media with year-over-year staggering increases in performance are coming to an end…and it is not all to blame on the economy. For example, consumers have become so desensitized to the clutter of banner ads that click-through rates are dismal, and retargeting is now the show pony, saving the day and keeping banners alive. However, with the continual threat of cookie deletion, multiple browsers, and the latest default setting of Mozilla to block cookies, “tracking” and “accountability” could have some challenges ahead.
While Internet usage has reached its saturation point, online ad spending continues to demonstrate healthy year-over-year growth rates and is not expected to dip to single digit growth until 2015, according to eMarketer. With online advertising spending reaching over $40 billion in 2013, we are experiencing a saturation point with these more sophisticated users and continual increases in advertising spending, which is leading to online confusion. With the growth of digital, the idea of a hyper-connected consumer 10 years ago is so outdated that nowadays consumers feel more disconnected than hyper-connected; there is always something they are missing out on, be it using one social platform vs. another, a missed promo code opportunity or daily/flash deal, or (GASP!) maybe a real-life event outside of their digital world.
As we attempt to take a step back and look at the big picture, here are a few things to consider:
- Ensure research is always part of what you are doing. Research is vital in staying up to date with competitors, consumer perception, and customer experiences; qualitative is just as important as quantitative. It is the grey that can fill in the gaps between the black and white story the data tells.
- Reconsider how you are measuring success. Does your current model for digital measurement only reward the “now,” or does it take into account the long-term health of the business and brand? Is your attribution model accounting for offline as well as online media?
- Consider consumer usage across devices and always work to make it better. Additionally, make sure that not only the experience is optimized for the device, but you are measuring performance and results accordingly. Lastly, do not neglect the opportunity to integrate social and local initiatives across these different devices.
- Evaluate your content strategy and its integration into all of your platforms and communications.
- Decide what you will be doing this year to truly enhance the overall consumer experience and value your brand offers them. Trust me, offering 40 percent off every week during the holidays truly sets an expectation for what “value” you can offer consumers moving forward. Take note and be mindful.
- Always allow for testing. You will never set the standard if you do not take chances and test to see what is working and what is not; however, you must make sure your test is set up for success, meaning: clear objectives, measureable results, specific differences in one experience vs. another, and the ability to confidently ensure the test will not create confusion for the consumer.
- Embrace the data. OK, now it may seem like I’m being contradictory. I’m not just talking about the data you use day in and day out, but digging beyond the high-level performance results. Data was definitely on trend for 2012, so there should be no shortage of it, but you need to be looking at it collectively across research, analytics, advertising, third-party, etc. This will help you to determine what to make a priority, what to test, and what perhaps can wait.
There is never a shortage of opportunities to test and try out. If you are always the “wait and see” follower brand you will never stand out amongst the clutter and chaos because consumers become desensitized so quickly. What is new one day becomes standard the next—who doesn’t have a responsive design site? So just like dieting, it’s important to keep a healthy balance and practice moderation to ensure you have a good mix of tried-and-true, and new and innovative that will keep you in shape to be sure you’re continually looking at the big picture for opportunities to embrace the change rather than waiting till it changes you.
This article was originally published on ClickZ on March 13th.
Tags: Advertising, Internet Statistics, Marketing, Optimization
Lessons from QCon: Building web applications that grow with your business
- By Kevin WEBBER | Technology July 9th, 2012
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I recently attended the first annual QCon held in New York City. I was fortunate enough to attend some excellent presentations from folks who design, build and operate some of the most heavily visited sites on the Internet: Twitter, Facebook, Etsy, and Netflix to name a few.
While the companies at QCon might all be in different businesses – from social networking to e-commerce to entertainment – they all have a few things in common: fanatical attention to detail, rapid delivery of enhancements, intolerance of wasted effort, a genuine understanding and appreciation of their users, and an intense focus on constant improvement. The end result is that all of their businesses are well regarded by not only their users but also by fellow software developers.
Twitter: It’s all about speed
Twitter is one of the most fascinating companies in the world. In a small amount of time they’ve tackled one of the most fundamentally challenging tasks humans have faced: scaling the delivery of information to a virtually unlimited audience. The challenge of sharing ideas with a wide audience was historically logistical in nature and tended to boil down to the cost of delivery; sharing a message with a few people was easy, but sharing a message with millions of people was difficult, time consuming, and expensive. Today, a message can be shared in virtually real-time with millions of people around the world just as easily as sharing the same idea with a few friends in your living room. This is a serious game-changer.So how does Twitter deliver a tweet from Lady Gaga to 20 million of her followers almost instantly?
Rather than use a single approach for all tweets and a single set of technologies, they define sensible boundaries within the overall system and optimize within those boundaries. Timeline, searching, and delivery are all built with completely different sets of technologies and considered separate concerns within the overall Twitter system. They use a blend of technologies such as Ruby of Rails, Java, and Scala to accomplish this. The use of multiple languages is commonly referred to as polyglot programming and is becoming a much more widely-used technique. Applications are becoming more complex, more heavily used, and more depended on being available 24/7.
Twitter also uses a few other very simple techniques like storing data in the same format that it’s read to avoid unnecessary processing at runtime. They also do something most engineers haven’t quite mastered the knack of; they handle traffic outliers like Lady Gaga differently than regular users like me. When I send a tweet to a handful of people, my tweet is processed using a general-purpose delivery mechanism that is good enough for average users and doesn’t consume too many resources. But a tweet from Lady Gaga is considered a special event from a technology perspective, because after all, it needs to be delivered to millions of followers.
Web applications are often implemented with a one-size fits all approach. For sites as heavily visited as Twitter, fanatically measuring usage is critical, and being able to adapt to unusual usage patterns like a tweet from Lady Gaga is critical to keeping Twitter fast and stable.
Etsy: Optimizing for happiness
Etsy is a remarkable company. Not only do they sell fantastic products from very creative craftspeople, but they also regard the act of writing code for their own site as an act of craftsmanship. Their blog, Code as Craft, is one of my personal favourites.Rather than use a customized general purpose e-commerce platform, Etsy built their own platform in-house using a set of simple technologies. Simplicity is what makes Etsy both remarkable and profitable. Rather than falling down the rabbit-hole of complexity, by keeping things simple they can rapidly enhance, maintain, and support a site that does some serious business: their merchants sold a combined $538 million of crafts in 2011. Just how rapidly do they deploy enhancements to the site? Over 20 times per day. In a single month, Etsy performs 300-600 upgrades. Rather than waiting months for the next quarterly release, at Etsy an idea can be planned, designed, built, and delivered in an afternoon.
How do they manage such a rapid evolution and keep both users and engineers happy?
- Everything is measured. A feature isn’t complete unless it outputs a wide array of graphs. Do users like the new feature? Are people viewing a page longer? Is the new feature impacting performance? These are questions Etsy engineers can answer within a few minutes.
- A new feature is gradually introduced. Features are initially rolled out to a select few users. A new feature is always implemented in a way so it can be turned off completely or gradually shown to more users over time after it has proven to be successful. Because Etsy deploys so many times per day, it is trivial to change the behaviour of a feature in a short period of time based on information gathered from real-world data. Only after a feature has proven to be successful is it rolled out to everyone.
- Speed is everything. Only essential elements of a page are rendered. Everything else is optional, from reviews to product recommendations. All optional page elements have a built in timer and a specified amount of time to finish processing. If they go over their allocated time, they are not displayed. Etsy engineers can predict how long each page will take to load with unwavering certainty. This is the attention to detail that makes people happy.
- Optimized for developer happiness. An application is often optimized for a computer, but sometimes a process that suits a computer doesn’t suit a person. Etsy optimizes for both computers and people because they understand the fundamental fact that joyful teams produce amazing software. This not only positions them to deliver great software, but because they are so well regarded by other software developers, they’re also in a position to hire the best and brightest engineers without relying on a Craigslist ad.
* Part 2 in this series will be published next week. Stay tuned!
Tags: Code as Craft, Etsy, Optimization, QCon, Twitter
Add a little chaos to your data
- By Amy MANUS | Analytics, Strategy June 21st, 2012
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Data is the hot trend for 2012. With digital efforts representing more of the brand budget, there’s a rush to figure out how to better optimize a fixed budget to drive bigger results. Anyone who has been in the industry long enough knows that regardless of what the data says, looking at it in different ways can usually shed light on a good story. In the competitiveness of marketing and advertising, we sometimes focus on our own performance and how good “we” did with a measurement of performance more reflective of corporate objectives.
According to the Forrester Consulting study “Data-Driven Design,” digital professionals stated the most important team performance metrics were the ability to complete projects on time or faster (65 percent) and the ability to complete projects on or under budget (64 percent). Trailing behind these metrics were things that truly impacted the customer, such as bringing to market new ideas. When solely focusing on speed and budget efficiencies as these numbers show, the best, most innovative solution might be hidden. These numbers only tell the story in black and white.
There is an abundance of data available from industry, business, customer, website, advertising, and social media. The attribution model is in overdrive attempting to crack the code of exactly where you should spend that extra dollar in an effort to increase productivity efficiencies and drive a stronger return on investment (ROI). While there are many types of data, looking at it in silos often leads to more tactical executions or optimizations to improve performance within that channel; however, in order to truly take a step back, you must first look at your objectives and complete an audit of all of your available data. This will allow you to look at the different channels and sources to begin to see a more holistic picture. During the audit, you can peel apart what key performance indicators (KPIs) are available within each source and what other variables could be valuable as well. While closely looking at the numbers, stories tend to emerge around areas of improvement and opportunity.
Additionally, we need to ask the bigger questions. How does this data relate to the overall business objective, customer experience, or key brand drivers? Or the most obtuse question: why should we care?
Taking the quantitative data and adding a little qualitative research can be extremely beneficial. While the data may tell you where there are issues with a specific part of a website, digging further through qualitative research or user testing can uncover “why” there is an issue. Qualitative analysis could include focus groups, user interviews, behavioural segmentation, usability testing, eye tracking studies, or ethnography. In order to tell the full story from beginning to end, we must understand the customer journey and take the data plus these additional insights to improve performance. This process doesn’t just hold true for website performance, but all customer touch points where we use data to evaluate performance.
We need to push it further. We need to find the opportunities to shine. Adding the “colour” to any project always comes with challenges. Holes are opened, and it gets messy. Typically, adding this colour can start with asking a few questions. Below are a few ways to add a little chaos that by no means saves money initially, but will make everyone a little smarter to save time and energy in the long run.
- Get other team members or departments involved. When analyzing the data, often including diverse teams offers a fresh perspective and alternative insights that were never considered. Also, it can work better to ensure solutions are not only answering current problems, but future problems as well.
- If something appears to be performing optimally, understand “why” it is; don’t just learn to prefabricate the situation.
- Continue testing regardless of how well the data is leading you to optimize. The digital world changes rapidly and what is optimal one day still has the opportunity to perform better.
- If the data can tell multiple stories, what is it really saying? Are there some unanswered questions that would be better served with a little multi-variable testing of some hypotheses rather than running with what appears to be the “winning” answer.
- Don’t get caught up in the big picture so much that you can’t move anything forward. A well-laid plan includes a roadmap with a better vision, but also includes quick wins and how that can play into feeding insights and performance in the future. No one likes a bottleneck.
At the end of the day, digging beyond the cold, dry numbers and looking outside the data can be so much more rewarding for employees. If it’s really done the right way, the consumer wins too.
This article was originally published on ClickZ on June 6th.
Tags: Amy Manus, Behavioural Marketing, Data Analysis, Data driven design, Data Mining, Measurement, Optimization, Qualitative Data, Quantitative Data, ROI
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