Victoria’s Secret Sauce – Web Analytics and Customer Experience Optimization

Introduction

Victoria’s Secret is a women’s fashion brand owned by parent company Limited Brands. As of January 2012, Victoria’s Secret has 1,017 stores with over 6 million square feet of selling space inside these stores. Inside a VS store, you will find a dazzling assortment of intimate apparel, beauty products, sleepwear, hosiery and more (About, 2012).

Victoria’s Secret Direct is the business arm that handles the Victoria’s Secret Catalogue and its ecommerce site, VictoriasSecret.com. VS Direct makes it possible for customers to have a great VS customer experience anytime and anywhere they want. The VS Catalogue reaches more than 390 million customers each year. The VS website and catalogue together brought in over $1.5 billion in net sales last year, a 4% sales increase (About, 2012).

Web Analytics Techniques the Company is Employing

Victoria’s Secret uses IBM Coremetrics to collect web analytics data from their website. VS began using Coremetrics in 2002, before the analytics company was bought in 2010 by IBM. Victoria’s Secret specifically uses Marketforce, a complete data capture, storage and decision-support system that gives companies knowledge of customer and visitor activity online. The Coremetrics marketing analytics platform captures and stores all customer and visitor clickstream activity to build LIVE (Lifetime Individual Visitor Experience) Profiles of online customers and visitors over time and across digital channels (Peters, 2002).

Fast forward 10 years, and now IBM owns Coremetrics and has integrated into the IBM Digital Marketing Optimization Suite, which itself is part of the IBM Enterprise Marketing Management Suite. Marketers are provided with a data warehouse on visitor’s digital journeys, across marketing touchpoints and channels, and even offline (IBM, 2012). Real-time KPIs and dashboards, mobile device analytics, powerful attribution capabilities, ad-hoc explorative analysis and reporting, segmentation capabilities, custom reporting are all features of the integrated Coremetrics platform.

How They Are Using Collected Data

The reason for Victoria’s Secret using analytics is to optimize the online customer experience and improve profitability. When they first began using Coremetrics, the goals were to use the knowledge gained to optimize the shopping path design, reduce website abandonment rates and improve retention marketing initiatives (Peters, 2002).

“We are very focused on customer service, with a firm commitment to making the online experience as rewarding for customers as our catalog and in-store experiences. Coremetrics provides extremely detailed analysis of our customers’ online behavior, delivering insights that help us improve the online shopping experience and run our web site more effectively. The combination of a rewarding shopping experience and increased efficiencies in managing our online channel has resulted in opportunities for revenue enhancement,” said Ken Weil, the vice president of new media at Victoria’s Secret (Peters, 2002).

Victoria’s Secret was ahead of its time in being this concerned with their online customer experience optimization. Many Internet retailers today still have not embraced the concept of customer experience optimization like they should be. Failing to realize how important the unique experience that customers have with your brand could be fatal in the competitive business environment today.

According to the Victoria’s Secret privacy policy, cookies and clear gifs are used to better understand website user behavior. Helping to improve the VS site, provide better customer service, personalize user’s online experience, and personalize offers based on user’s unique tastes, interactions and purchase history are all ways that VS uses the data it acquires about customers and website visitors (Privacy, 2012).

Tools, Data Collection Methods, or Metrics that Could Improve Overall Web Analytics Efforts

Since Victoria’s Secret spent about $12 million on the Victoria’s Secret Fashion Show this year that aired on CBS on December 4, VS marketers should collect data and follow metrics that are specifically for the fashion show. According to financial analysts, the show pays for itself as a marketing tactic because of the sales increases that occur during and after the fashion show (Maheshwari, 2012).

According to Ed Razek, Chief Marketing Officer of creative services of Limited Brands, “you see sales results almost immediately. On the night of the show you see substantial increases in our web business from all of the news coverage. The day after the fashion show runs on television, you see substantial increases in our web business” (Amed, 2011).

Sales increases are great, but the VS Fashion Show is about more than just sales increases—it is the cornerstone to the VS integrated marketing communications strategy that drives brand awareness as well as sales across retail, catalogue and online channels. According to a Dartmouth case study, when Leslie Wexner bought Victoria’s Secret, he wanted to make it “stand out as an integrated world-class brand. The same products are launched at the same time, in exactly the same way, with the same quality and positioning” (Durbin, 2002).

Since VS has both sales and brand awareness goals associated with the VS Fashion Show, these goals should be connected to web metrics that can measure them. I would find a way to measure all inbound traffic sent by the fashion show. A specific landing page for people visiting the website because of the show would separate traffic generated from the show from regular traffic. Brand awareness could be measured by quantifying the social media mentions, posts and conversations that have to do with the VS fashion show. Sentiment analysis for specific show-related keywords could show the lift that the VS brand receives because of the show.

Conclusion

Victoria’s Secret is doing many things right, and they are way ahead of many other Internet retailers when it comes to optimizing their customer experience. But there are always improvements that can be done, and I think using web metrics to show how successful the Victoria’s Secret Fashion Show is something VS marketers should definitely do.

References

About Victoria’s Secret. (2012). Limited Brands. Retrieved on 12/10/12 from http://www.limitedbrands.com/our_brands/victorias_secret/about.aspx

Amed, I. (21 November 2011). Addressing Fashion’s Communications Conundrum. The Business of Fashion. Retrieved on 12/10/12 from http://www.businessoffashion.com/2011/11/addressing-fashions-communications-conundrum.html#more-26875

Durbin, T. (2002). Victoria’s Secret. Tuck School of Business at Dartmouth: Center for Digital Strategies. Retrieved on 12/10/12 from http://digitalstrategies.tuck.dartmouth.edu/cds-uploads/case-studies/pdf/6-0014.pdf

IBM Digital Analytics. (November 2012). IBM Software Data Sheet. Retrieved on 12/10/12 from http://public.dhe.ibm.com/common/ssi/ecm/en/zzd03044usen/ZZD03044USEN.PDF

Maheshwari, S. (20 November 2012). The marketing secrets of Victoria’s Secret. Chicago Tribune. Retrieved on 12/10/12 from http://www.chicagotribune.com/business/ct-biz-1120-bf-secret-marketing-20121120,0,5870626.story

Peters, K. (29 July 2002). Victoria’s Secret Selects Coremetrics to Optimize the Online Customer Experience and Improve Profitability. Internet Retailer. Retrieved on 12/10/12 from http://www.internetretailer.com/2002/07/30/victoria-s-secret-selects-coremetrics-to-optimize-the-online-c

Privacy Statement. (26 October 2012). Privacy & Security. Victoria’s Secret. Retrieved on 12/10/12 from http://www.victoriassecret.com/privacy-and-security#technology

Goals, Funnels & Filters in Google Analytics

Introduction

Google Analytics provides many different metrics about your website visitors. Audience demographics, behavior and ecommerce information are just some of the useful metrics available in GA. But what if you need information on a specific event, like a conversion? Or what if you want to drill further down into your data? Or what if you need to have more control over segmenting your visitors?

Well Google Analytics has an answer to these questions, and they are goals, funnels and filters. All three of these help you to better understand your website visitors, and they are discussed further below.

Goals

Defining the goals of a website is one of the best ways to track and measure the effectiveness of your website. Goals should be tied to your business objectives that the website is supposed to accomplish, whether that is selling a product or gathering leads for follow-up sales calls. Goals can be set up in Google Analytics to track exactly what is important to your business. All websites should have at least one goal.

In Google Analytics there are four types of goals that can be created and tracked: 1) a URL destination goal, 2) a Time on Site goal, 3) a Pages/Visit goal, and 4) an Event goal (Goals, 2012).

A URL destination goal triggers a conversion when a visitor views a specified page on your website after completing a specific activity, like filling out a form, downloading a whitepaper or purchasing a product (Goals, 2012). As an example, we will use a company that has a website with the purpose of collecting sales leads. The main goal for this website should be users filling out the sales call request form. This goal can be set up by going to the Goals section in Google Analytics.

Time on site and pages per visit goals are useful for measuring website engagement. If you have content website and your objective is to get users to view as much content as possible, a pages per visit goal would be a good one to track.

There are numerous metrics that are tracked for each goal that is set up. Number of goal competitions, goal value in dollars, goal conversion rate and total abandonment rate are all metrics that are tracked for each goal. The source or medium for each goal completion is also tracked, along with the goal completion percent for each source or medium. This enables businesses and marketers to compare the goal conversion percent for each source and medium that sent traffic that lead to a goal conversion.

Funnels

For each goal, you can define a funnel, which is the path you expect your website visitors to take on their way to completing a goal (Lesson 6, 2012). There is a report called Reverse Goal Path that can also provide useful information about your website’s goal conversions. This report shows you how many users converted from each path. This can help you recognize funnels that you had not previously considered (Goals, 2012).

Multi-channel funnels are another type of funnel that shows how different traffic sources work together to create sales and conversions (About, 2012). I discussed the multi-channel funnels report last week, including how calculating the Return on Investment (ROI) of each channel can help you understand which channels are performing the best.

I also spoke about the importance of useing the multi-channel funnel report to spot trouble spots in your business’s conversion funnel. Spotting the point where potential customers are dropping out of the conversion funnel, and fixing whatever the problem is, can instantly raise your websites conversion rates. For example, if a lot of potential customers are dropping off on the page that asks for shipping information, maybe there is something wrong with that page, or maybe people think you are charging too much for shipping. Do some tests to find out. Make a discounted or free over a certain amount spent shipping campaign to see if that reduces the drop-offs on that page.

Filters

In Google Analytics, filters allow you increased flexibility with your data by letting you define what data is included in your report and how it appears. You can use filters to customize reports so that the most useful data is highlighted. Some popular uses for filters are removing traffic from internal company sources, restricting data for a profile or user, segmenting data and customizing data. The two types of filters are predefined filters and custom filters (Filters, 2012).

There are three types of predefined filters: 1) exclude traffic from domains, 2) exclude traffic from the IP addresses, and 3) include only traffic to the subdirectories (Filters, 2012). As a best practice Google recommends excluding all website traffic from inside your company because including this internal company traffic will not give accurate measures of your target market’s website behavior.

Custom filters offer you greater control of what data appears in your Google Analytics reports. Exclude, include, lowercase/uppercase, search & replace, and advanced are all types of custom filters. The exclude and include filters are the most common filters used, and are often used to segment data by geographical region (Filters, 2012).

By using profiles and filters, you can customize your data views. For example, you can create separate profiles with filters that segment traffic by referring source, geography or user-defined variable. Google recommends always keeping one profile with all your data, so that you always have access to all your data. Here is a visual that shows the example segments created with profiles and filters (Filters, 2012):

Using filters, you can set up a profile that only includes traffic sent by Google AdWords. This will help you to better analyze the website traffic that AdWords is sending your way. Another custom filter that will help businesses make better decisions is segmenting by geographic region. For example, say a company has four sales regions— Northeast, Southeast, Northwest and Southwest, and they need to know website metrics on each of these regions. Using filters is an effective way to segment website visitors so that each segment may be analyzed.

References

About this report. (2012). Multi-Channel Funnels. Google Analytics. Retrieved on 12/3/12 from www.google.com/analytics

Filters in Google Analytics. (2012). Google Analytics IQ Lessons. Google Analytics. Retrieved on 12/3/12 from http://www.google.com/analytics/iq.html

Goals in Google Analytics. (2012). Google Analytics IQ Lessons. Google Analytics. Retrieved on 12/3/12 from http://www.google.com/analytics/iq.html

Lesson 6. (22 October 2012). P.I. Reed School of Journalism. WVU. Retrieved on 12/2/12 from eCampus.

Customer Insight with Google Analytics

Introduction

Google Analytics is a great tool that can help businesses understand their customers, so they may better acquire and retain customers. Understanding customers’ digital behavior can help marketers to create more effective marketing campaigns. I choose all the metrics below to discuss because of the great ways they can specifically make a marketing campaign more effective.

Visitor Location

Knowing the different locations of people visiting a business’s website can help with numerous marketing decisions that must be made. The first is deciding in which locations to market your company’s products and services. For example, an ecommerce business trying to decide where to spend its online advertising budget could consider the locations of the people visiting the business’s website when making this decision. If a large percentage of website visitors are coming from New York, San Francisco and Chicago, showing online ads to people in these locations could produce better results.

Combining website visitor location information with keyword analysis may produce even better results. For example, if the ecommerce business also found that a lot of people are searching for their top three keywords in Chicago, it may be worth it to make the ad budget for this location higher.

Mobile Website Metrics

According to recent research from Pew Internet & American Life Project (Duggan, Rainie, 2012), 85% of U.S. adults now own a mobile phone of some kind. People are attached to their smartphone and many never leave home without it. This helps to explain the huge growth in mobile internet usage recently. According to ComScore (Flosi, 2012), 52.6% of total U.S. mobile subscribers used their phone’s browser from June 2012 to September 2012, up 2.4% from the three month period before. Millions of people are using their mobile devices to access the Internet; it’s time that businesses and marketers start to pay more attention to these mobile Internet users, because they are growing by the day.

Google Analytics is a great tool to use when trying to figure out the mobile website behavior of your customers. Using the advanced segments button in Google Analytics, choose mobile traffic. Tablet traffic is also a visitor segment that should be analyzed separately from other visitors. People accessing your website from a mobile phone and a tablet may want different things from your website and the only way to find out is to analyze these visitor segments separately.

Specific metrics that should be looked at for mobile website visitors are site content and traffic sources. Many times when people come to a mobile website from a smartphone, they are in the middle of a trying to accomplish a task, like calling to order food for example. Because of the on-the-go nature of smartphones, information like telephone number, hours of operation, address and services offered needs to be easily viewable from a mobile website. By analyzing the website content that mobile visitors are viewing on your business’s regular website, you will know what they are looking for and can place this information where it is easily accessible on your mobile website.

Traffic Sources

Understanding what digital platforms are sending traffic to a website is critical to making decisions about which platforms to market and advertise on. As an example, we will say that a marketer needs to know which keywords provide the most web traffic organically, so that the keywords may be prioritized and included in the business’s content strategy. Under the traffic sources tab in Google Analytics, you can see exactly what keywords lead website visitors to your website and how many visitors were brought by each keyword. With this information, a marketer can prioritize organic keywords and then create website and blog content that includes the best keywords.

Knowing which social networks drive the most traffic to your website is another insight that the traffic sources information on Google Analytics can give you. Under the social sources tab, a marketer can see the various social networks that drive traffic to their website. This information could be very helpful when deciding which social networks to expand your business’s online presence to.

Multi-Channel Conversion Funnels

Multi-channel funnels show how referrals and searches contribute to the sales of products and services. This funnel looks at the sequence of clicks in the 30 days leading up to each conversion and transaction. Data for this conversion path comes from sources such as paid and organic search keywords, referral sites, affiliates, social networks, email newsletters, and custom campaigns that have been created, like an offline campaign that sends traffic to a vanity URL (About, 2012).

In the multi-channel funnel report, channels are credited according to the roles they play in conversions. Assisted conversions shows how many conversions each channel initiated, assisted and completed, and their value. The top conversion paths report shows the conversion paths that customers took on their way to a purchase (About, 2012).

Knowing the exact online actions your customers took before making a purchase can help marketers in many ways. First, if you know what channels are creating the best ROI, you can invest more of the marketing and advertising budget into these channels. If done correctly, this will raise the ROI of your marketing as a whole, because you will be spending less money with channels that don’t work as well as others. To determine the ROI of each channel, use this ROI formula for marketing investments: (Return – Investment)/Investment. For example, if a marketer made $100,000 in sales from a marketing investment of $10,000, the formula would look like this: (100,000 – 10,000)/10,000 = 90,000/10,000 = 9. Multiply the answer by 100 to get a percent and you have 900%. This means the marketer made 9x in sales what was spent on marketing. By doing this for each channel, you can compare apples to apples and really know which channels are working best for your products, customers and business.

Another way to use this information is to try and spot trouble spots in your multi-channel funnel conversion paths. For example, if you notice that a good percentage of people are dropping out of the conversion funnel at a certain point, investigate this to find out why, so you may fix the problem. To do this, go through the conversion funnel yourself and when you get to the point that people are dropping off, look around and search for what could be causing the drop off. It could be something as simple as a broken link and you would have never known.

Conclusion

Analytics and metrics are critical to understanding your customers and the effectiveness of your marketing campaigns. Any business with a website should be using Google Analytics to gain better insight in to their customers and marketing effectiveness.

References

About Multi-Channel Funnels. (2012). Google Analytics Help. Retrieved on 11/26/12 from https://support.google.com/analytics/bin/answer.py?hl=en&utm_id=ad&answer=1191180

Duggan, M. & Rainie, L. (25 November 2012). Cell Phone Activities 2012. Pew Research Center’s Internet & American Life Project. Retrieved on 11/26/12 from http://pewinternet.org/~/media//Files/Reports/2012/PIP_CellActivities_11.25.pdf

Flosi, S. (2 November 2012). ComScore Reports September 2012 U.S. Mobile Subscriber Market Share. ComScore. Retrieved on 11/26/12 from http://www.comscore.com/Insights/Press_Releases/2012/11/comScore_Reports_September_2012_U.S._Mobile_Subscriber_Market_Share

Google AdWords vs Facebook Ads

Google AdWords

There are numerous things that are different, and a few things that are the same with Google AdWords and Facebook Advertising. The payment model is the exact same for both advertising services. Both operate on either a CPM, which stands for click-per-thousand impressions, or a CPC model, which is cost-per-click. Advertisers set up a budget that they are willing to spend per day, and set an amount that they will spend per click or thousand impressions. Google pioneered this advertising model and now Facebook uses it as well.

According to a Google AdWords video (GoogleBusiness, 2009), advertisers can quickly make changes to ads and campaigns at any time. This is great because it allows advertisers to make real-time changes when needed. For example, say a certain keyword is performing better. The advertiser may want to raise the CPC and daily budget for this keyword so that more people click through the ad. Advertisers can start and stop ads and campaigns at any time.

There is no minimum budget for Google AdWords, so businesses can spend as little or as much as they would like (GoogleBusiness, 2009). This is great because it enables businesses of all sizes, large and small, to be able to afford advertising with Google. It used to be that only big businesses with big advertising budgets could afford advertising, but now anyone can because the cost to advertise with Google AdWords is so low.

It is easy to reach large or small audiences with Google AdWords based on the keywords you choose to advertise with. You can reach millions of people in the U.S. and around the world. Ads can be geo-targeted based on a user’s location on a local, national or international level. For example, your audience can be as specific as people searching for dog toys within 20 miles of San Francisco (GoogleBusiness, 2009).

Google AdWords gives advertisers quick access to campaign data, so that smarter advertising decisions can be made.

Facebook Advertising

Like I stated above, Facebook shares a payment model with Google. The CPC and CPM models are how advertise pay for ads on Facebook. Just as with Google, advertisers set a price they are willing to pay per click and a maximum budget for each day.

On Facebook, advertisers can advertise a Facebook page, an app, an event, a group or a website (FacebookTutorial, 2010). Facebook also offers ads called Sponsored Stories, which is when the advertiser promotes likes or check-ins in their friends’ timelines (Facebook Marketing, 2011). This allows marketers to really promote the word of mouth recommendations happening all the time on Facebook. The Sponsored Story appears at the top of the feed, so it is more likely to be seen by the user.

Marketers can target over 1 billion Facebook users by country, state, province, city, age, sex, interested in (males or females), relationship status, languages spoken, likes and interests, education and work, connections on Facebook, and friends of connections (FacebookTutorial, 2010). Because people post so much personal information on Facebook, these targeting options can be very useful to marketers who know exactly who they want to target and their characteristics. Google does not have this wealth of demographic and psychographic information like Facebook does, and this is one advantage Facebook advertising has over Google. Google’s ads are based on a person’s intent when searching for different keywords; Facebook’s ads are based on its deep knowledge of each user’s personal interests, likes and preferences.

References

GoogleBusiness. (15 June 2009). Getting Started with Google AdWords. Retrieved on 11/12/12 from http://www.youtube.com/watch?v=tx2L6EGa9DY

FacebookTutorial. (5 April 2010). Facebook Tutorials – How to Advertise on Facebook. Retrieved on 11/12/12 from http://www.youtube.com/watch?v=8jOBDIql4yc

Facebook Marketing. (25 January 2011). Introducing Sponsored Stories. Facebook. Retrieved on 11/12/12 from http://www.facebook.com/video/video.php?v=10100328087082670

Content vs Conversation + Mobile

Content Sparks Conversation

I do not see this as a one versus another debate. This is how I see the relationship between the two— you must bring great content to the conversation, and this will hopefully bring the conversation to your great content, and then your products, brand and company.

Greenburg (2009) states that “without content, there is not a whole lot to talk about” and I agree with this statement. Content is what lights the spark of conversation in social media. If content, including writing, photos, video and audio, is not interesting and relevant to readers, it will not spark too much conversation because no one will have anything to say about it. On the other hand, if content is well-targeted to readers, interesting, relevant, and useful or entertaining, some people will be moved enough to comment, reply to or like your content. Content sparks conversation.

The conversation itself is important as well when trying to build relationships with customers in this new social era we are all operating in. People post comments and questions on social media, talking to a company, and expect to be answered in a timely manner by someone with the company. And not just anyone at the business, someone that actually has the authority to fix their problem.

Responding to all user posts and mentions on social media is something all companies should be striving for. Not responding on social media is equal to ignoring someone on the street talking to you, which we all know is rude. Yet some companies ignore customers on social media every day. If a business is trying to start a conversation around its brand, products or company, goal number one should be to respond to all mentions that are questions or inquires.

Content Consumption on Mobile Devices

I think the real question communicators should be asking is—how must our content change to adapt to mobile? Smartphone and tablet usage has continued to grow exponentially since 2007 when the iPhone was first launched. The adoption and usage of mobile devices has shown no sign of slowing down. Currently, 119 million people, or 51% of the U.S. populations own smartphones (Flosi, 2012). Businesses need to accept the fact that mobile is an essential part of future content consumption, and figure out how to create a positive user experience for their content on mobile devices.

Many content marketers still do not have a mobile website or mobile app. I get so annoyed when I see a headline in my Twitter feed on my phone that I really want to read, and I click through to read the article, and I cannot see the text because it is so small, or even worse, the mobile website is not even functional. I have literally given up on some well-known blogs and websites on my phone until they create a mobile version (which many of them have not done yet).

The mobile traffic to the Forbes website has grown from 10% to 25% in just 10 months, and Chief Product Officer Lewis D’Vorkin says “there’s no question that our mobile traffic will continue to rise” (O’Regan, 2012). This is just one of many examples of the huge growth in mobile content consumption. According to ComScore (Flosi, 2012), 54% of smartphone owners use mobile apps, 52.6% use the browser, and 39% access social networking websites or blogs from their mobile device. Companies must starting preparing, testing and trying to figure out mobile content consumption now.

References

Greenberg, M. (20 October 2009). Content is King of Social Marketing. Multichannel Merchant. Retrieved on 11/2/12 from WVU eCampus.

O’Regan, R. (19 September 2012.) 3 Reasons to adopt a “mobile first” strategy. Emedia Vitals. Retrieved on 11/12/12 from http://www.emediavitals.com/content/3-reasons-adopt-mobile-first-strategy

Flosi, S. (2 November 2012). comScore Reports September 2012 U.S. Mobile Subscriber Market Share. ComScore. Retrieved on 11/12/12 from http://www.comscore.com/Insights/Press_Releases/2012/11/comScore_Reports_September_2012_U.S._Mobile_Subscriber_Market_Share

Conversion Rate Optimization

Conversion Rate

Conversion rate is defined as the ratio of conversions over a relevant denominator, such as the number of visitors to a website (Web Analytics Association, 2008). The conversion rate of a website or landing page is arguably the most important metric a marketer has to analyze because a conversion is the goal of the website or landing page being achieved.

A conversion does not only mean a purchase; it can mean different things to different businesses with different types of websites. For an ecommerce website, a conversion would be a completed purchase, but for a website that does not sell anything, and instead generates leads for follow-up, a conversion would be a form submission.

According to a SEOmoz (Stephen, 2010) article, conversion rate optimization is finding out why visitors aren’t converting, and fixing it so they do convert. This means that optimizing conversion rates leads to increasing conversion rates.

There are numerous benefits that companies can gain from optimizing the conversion rates of their websites and landing pages. The most important benefit is sales increases from the higher percentage of people that purchase products or become a lead on the site. In addition to making more money, increasing the conversion rate makes your marketing spend more effective and increases the ROI of your marketing efforts. Higher conversion rates can lead to an increase in market share because more people are buying your products instead of the competition’s products.

Research & Analysis in Conversion Rate Optimization

There are five recommended steps for optimizing the conversion rates for websites and landing pages. They are research and analysis, solutions, development and testing, review and expand, and repeat (Stephen, 2010). Today I will discuss the first step, research and analysis of the website.

Step one, research and analysis, includes numerous ways to uncover hidden problems that could be keeping website visitors from converting. The writer advises to “become the customer” and actually buy your own product or service from your own ecommerce website (Stephen, 2010). Take screenshots along the way to document the process.

Goals and funnels should be set up in Google Analytics to show where you’re losing traffic and where the largest opportunities are. Other analytics packages should also be used to supplement Google Analytics, such as Crazy Egg, which generates heatmaps of the website, and ClickTale, which shows how far down the page users are scrolling and records videos of user sessions (Stephen, 2010).

The writer recommends doing five usability tests. There are numerous affordable usability testing companies including UserTesting.com, which only cost around $40 for a 15-minute usability test. You will get a video of their session and the voiceover as they navigate the website (Stephen, 2010).

Other suggested ways to find problems with a website is surveying customers to see if there are usability issues that make it so a user can’t buy, or if there are objections and users won’t buy. SurveyMonkey, Kampyle or a phone call to a customer will do the trick. Make sure customers can give open-ended answers to questions so they may tell you their opinions in their own words. Talking to sales staff can also be helpful. Ask them what questions and objections customers frequently come up with (Stephen, 2010).

References

Web Analytics Association. (22 September 2008). Web Analytics Definitions. Retrieved from eCampus.

Stephen. (26 April 2010). The Definitive How-To Guide for Conversion Rate Optimization. SEOmoz. Retrieved from http://www.seomoz.org/blog/the-definitive-howto-for-conversion-rate-optimization

Using Predictive Analytics to Predict Customer Behavior

Web Analytics and Predictive Analytics

In Chapter 3 of Web Analytics 2.0, Kaushik (2010) discusses diagnosing the root case of a metric’s performance by using predictive analytics. He gives an example using an ecommerce website that wants to improve its conversion rate by 10%. Kaushik (2010) recommends going through a “root cause diagnosis exercise.”

Before figuring out how to improve the conversion rate, all the variables that influence or have an effect on the conversion rate must be identified. Examples of these variables are acquisition strategy, organic search keyword ranks and the ease of your checkout process. Once all the influencing variables are identified, data must be collected for each of the variables. Than all the variables must be analyzed to determine where the true opportunities are for improving the ecommerce site’s conversion rate (Kaushik, 2010).

According to Kaushik (2010), the output of this exercise will be something like this: here are three areas where the ecommerce site stinks. Then a cost-benefit analysis can be done to figure out which areas will give the maximum bang for your buck.

This is a great example of how using predictive analytics can help market a business. There are numerous other ways that predictive analytics can be applied to marketing situations to help marketers make better decisions and communicate more effectively. The one I will discuss today is customer profiling and segmentation.

Predictive Analytics and Marketing

Wouldn't every business like to know which of its customers are the most profitable? And what their characteristics are so more customers like them can be found? Of course they would, and this is why marketers are so interested in predictive analytics for customer profiling and segmentation.

According to an SAS whitepaper, classification trees or logistic models can be used to help companies understand their customer base by segmenting customers based on measures that matter to the business, such as response, revenue and risk (Parr-Rud, 2012).

For example, a technology company is preparing to launch a campaign for a combination printer/fax/copier targeting a list of current business customers. To group customers into three distinct groups, two models were created. A logistic regression model predicted the likelihood that the customer would buy the printer, and a linear regression model estimated the amount the customer would spend, given that a purchase is made. The product of these two scores gave each customer an expected value. The company then divided its customer list into groupings that allowed marketers to create a strategy based on the customer’s expected value (Parr-Rud, 2012).

In addition to better targeting customers for their new product, the company also used the firmographic profile of the highest value customers to identify new target markets for acquisition marketing (Parr-Rud, 2012).

This is a few of the ways predictive analytics can be used to determine and predict customer behavior.

References

Kaushik, A. (2010). Web Analytics 2.0 The Art of Online Accountability & Science of Customer Centricity. Wiley Publishing, Inc.

Parr-Rud, O. (2012). Drive Your Business with Predictive Analytics. SAS Whitepaper. Retrieved from http://www.sas.com/reg/wp/corp/42596