6 Content Generation Styles

Here are 6 content styles that can be used for content marketing programs:

Newsroom Model

  • Generates social content in near real-time.
  • Content plays off the news agenda or a brand narrative to drive a complementary “conversation agenda.”
  • The Newsroom model can drive content and conversation across owned, earned and even paid platforms and channels.
  • This model requires qualified “brand journalists” used to creating high-quality, multimedia content on an ongoing basis.

Real-time Marketing Model

  • Using the Real Time Model, you can take continuous advantage of fast moving cultural trends for marketing purposes – leveraging the wave of earned media and timely buzz to help propel an asset or discussion.
  • This requires a established team or clear work flow to react to the digital buzz.

Curator Model

  • Brands set up a compelling co-creation or crowdsourcing concept and rely on consumers to submit the majority of the content experience.
  • Light curation or editorial from the brand guides the content experience.
  • Curation often requires strong content and influencer management skills as well as filtering software (think Mass Relevance) to scale the operation.

Partner Model

  • Allows brands to work with established media to collaboratively develop high quality, co-branded content.
  • In many cases the partner is primarily responsible for creative, production and scale. The partner generally delivers a high-reach distribution channel, as well.

Lead Gen Model

  • Social/search data and specially developed content narrowly target B2B or niche prospects and drive them towards a lead generation behavior.
  • Clearly, a B2B orientation helps, as well as the ability to create valuable “paywall” or “lead-wall” content.

Community Platform Model

  • Provides a scaled approach to creating fresh content for existing social and digital platforms, or existing owned communities.
  • Production is done by social content specialists – translating to high quality on shorter timelines.
  • This model relies on a strong Community Director with their finger constantly on the pulse of their community.

Site Search Analytics

Here are my notes on Site Search Analytics.

The main Analysis are detailed below:

Search Metrics – Goal Based Analysis

% Queries that retrieve zero results

–       Measures the quality of your search results, based on the degree to which your search results are failing.  Typically used as a KPI.

–       Zero queries generally mean failure, so your goal should be to make this number as small as possible.  Exception is when users are simply trying to validate that a piece of content does not exist.

% Queries where users click on a search result

–       Measures the quality of your search results based on the degree your results are being clicked on by users.

–       If a search result is clicked, it’s likely that it’s at least interesting and engaging, even if irrelevant.  So no clicks may mean poor results

% Queries that lead to users exiting the site

–       Aka – search bounce or site search exit rate

–       Measures the quality of the overall search experience based on the degree users leave without clicking on any results.

–       When users immediately leave your site after searching, it can infer that their expectations were not met.

% Sessions that use Search

–       Compares the usage of your site’s search system versus browsing.

–       Knowing the degree of which users rely upon search helps determine how much you invest in developing and improving your search system.

Average # queries per session

–       Tracks how frequently users search during a single session.

–       Most useful when cross-referenced with specific keywords that are being used within a single session (see Search Refine Rates)

–       If the queries are duplicates or synonyms, users may be flailing, indicating poor search performance.

Average # search results pages viewed per query

–       Measures the quality of search results.

–       If the number is greater than one, users may not be finding the most relevant results on the first page.  Keep in mind that this measures the performance of individual queries, rather than your site overall.

Average # pages viewed after searching

–       Measures the quality of your site’s content and calls to action.

–       The act of searching itself is only a step in the process.

–       What did users do after they searched?  Did they take the action you hoped they would?

–       Compare this metric with Average # Pages viewed before searching

Average time spent on site after searching

–       Measures users level of engagement and satisfaction after search.

–       The more time users spend on your site is often – though not always – a good indicator of their satisfaction level.

–       Temper this assumption by cross-referencing this metric with others. Such as Average # pages viewed after searching and goal/conversion completion rate.

Average time spent on site before searching

–       Measure the effectiveness of your site’s navigation

–       Often users will search when they become frustrated; knowing what that threshold is can help inform your design decisions.  Compare this metric with Average time on site without search in conjunction with goal/conversion completion rate.

Average time spent on each search results page

–       Measures the usability of your site’s search engine results pages.

–       Longer times might be an indicator that your SERP design is confusing or contains too much information.

–       Follow this metric over time to see if it goes up or down in response to your design tweaks.

Conversion ratio visitors who use this site search

–       Measures the quality of the overall search experience, compared to those who browsed.

–       This is another way to look at how well your site’s search is performing compared with this its browsing experience.

Average # items added from search results

–       Measure the number of items marked or added to cart after using search.

–       Applicable for sites that have a shopping cart or similar “basket” functionality.  Use in conjunction with other metrics, such as Search conversion rate, Top search terms with corresponding conversion rates, and Average time spent on site after searching to make a case for greater investment in your system.

Session Duration for all sessions that included searches

–       Measures the average time spent on your site for users that searched.

–       Compare with Session duration for all sessions that didn’t include search to get a good sense of whether users are exploring more or less with search than with browsing.

–       Considering your site’s goals, is this a good thing?

Search Conversion Rate

–       Measures the overall percentage of searches that result in a conversion.

–       Helps determine how many users “converted” using search. The term conversion can go beyond making purchases; conversions can also include downloading, signing-up, registering, and other actions

Search refinement rate

–       Measures the quality and relevancy of search engines result pages related to a user query

–       High rates of refinement typically mean that the SERPs did not meet the users’ expectations and that user are continuing to seek results despite their poor experience.

Most Frequent Search Terms

–       Tracks the most commonly searched queries.

–       You should know your top queries by heart, as they are the most popular and , likely, the most valuable to your site’s users.

Most frequent queries with corresponding conversion rates

–       Track the overall performance of your most common queries.

–       The term conversion can go beyond making the purchases; conversions can also include downloading, signing-up, registering, and other actions.

–       Follow these queries overtime to understand your users needs, especially queries that are frequently searched and evergreen.

Most frequent pages on the site where site was initiated

–       Tracks the quality of content, design, and page (CMS) templates.

–       Shows where users became frustrated with content or navigation and decide to begin searching.  Learn more by determining if these pages are related.  Do they share the same design? Or CMS template?  Note that if search is the user’s first action on the site, it should not be included in this metric.

Total # of unique searches

–       Measure the breadth and depth of your users’ natural language.

–       By itself, this doesn’t mean people, but when it is broken down and examined, it’s probably the most valuable list you will come across because it is your users’ confessions of what they are trying to find in their own words.

–       This is a gold mine of data that can be directly applied to keywords, metadata, SEO, SEM, navigation, taxonomy, page titles, tags etc.

This is valuable data to apply for greater findability, accessibility and relevancy.

Universal Analytics – Custom Dimensions and Metrics

I’m trying to learn how to configure Universal Analytics so I can identify particular audience segments.  The visitors will define themselves by taking certain actions on the website (e.g. visiting a certain page or by tracking an event).

Note: Event tracking – if you’re having problems using Universal Analytics with onclick event tracking try onmousedown instead.

You can create custom dimensions (rows) and metrics (columns) in UA.  And there are 4 main steps.  But its worth starting off reading the  Reference Guide first.

Step 1: Configure a Dimension or Metric through the UA Interface.

Step 2: Configure your web property to identify users actions on certain page elements as a dimension

Step 3: Set up a new custom segment in Advanced segments so you can analyse the data via that segment.

Step 4: Analyse your data

1. CONFIGURE UA Custom Definitions

For me, I’m trying to identify user status by recording what actions they take on the site.

1. Registered Users – people who have registered to use the site but not paid the full subscription

2. Members – people who have subscribed

To do this I need to set-up a dimension in the GA interface.  The thing to remember here is that you only need to set-up one dimension (index) for both audience types.  You differentiate between them by assigning different “dimension values” when you tag the action on your site in the next step.

This article describes how to set-up the Dimension in GA:

https://support.google.com/analytics/answer/2709829?hl=en&topic=2709827&ctx=topic

2. CONFIGURE WEBSITE

For this experiment, I’m using two techniques – Page View and Events to define users.

Page View Tracking Method

To set up a page view to define a user (e.g. every time a visitor views the confirmation page you want to label them as a customer) you need to update the GATC in the header.

Specifically, you update the page view function to include dimension and value.  So this piece of code in the header GATC:

ga(‘send’, ‘pageview’);

Becomes:

ga(‘send’, ‘pageview’, {‘dimensionX’:  ‘dimensionValue’});

You just need to update the dimension ‘X’ index and the dimension value.  For example:

ga(‘send’, ‘pageview’, {‘dimension3’:  ‘customer’});

Event Tracking

Alternately, you may want to define people when they click on a button or particular page element.  You can use event tracking for this.

Note: You may need to test using onclick or onmousedown to call the event.  I get varying results but onmousedown appears to work well.

To do this you take the event tracking code and customise it to include the dimension and value:

Standard event tracking code with dimension extension

<a onmousedown=”ga(‘send’, ‘event’, ‘category’, ‘action’, {‘dimensionX’: ‘dimension value’});” href=”XXXXX.html”>XXXXX</a>

Configured code

<a onmousedown=”ga(‘send’, ‘event’, ‘Registration Button’, ‘Submit’, {‘dimension3’: ‘Registered’});” href=”buy.html”>onclick customer 555</a>

3. CONFIGURE SEGMENTS

In GA Reporting Interface Select > Advanced Segments > + New Custom Segment.

Fill out form to “Include” your “Dimension” (which will be in the list exactly as you named it when you set it up in step 1) and then set it to “Contain” your dimension value (e.g. ‘registered’).  Hit > Save or Test to see if it works….

If it works, when people hit the conversion action you can segment the data by this dimension and you can see how all the reports perform by uses in this segment.

Custom Dimensions Links

How to guide:  https://developers.google.com/analytics/devguides/collection/analyticsjs/custom-dims-mets#implementation

Set-up: https://support.google.com/analytics/answer/2709829?hl=en&topic=2709827&ctx=topic

Reference Guide: https://developers.google.com/analytics/devguides/platform/features/customdimsmets

Email Analytics

Measuring the response of email campaigns need to take into account the full user journey.  This starts with Campaign Response – how many people respond to your email and how many you retain for future campaigns.  Then you look at Website Behaviour – how do users engage.  This can be a measure of quality of your email lists or the quality of your landing pages and website content.  Finally, Business Outcomes – the hard end of your campaign – does it work, does sell products?

Campaign Response

Delivery Rate = (# of emails – # of bounce backs)/ # of emails sent

Open Rate = # of emails opened / # of email sent

Click-to-open rate (CTOR) = # of clicks / # of emails opened

Subscriber retention rate = # subscribers – bounce backs – unsubscribers / # subscribers

Website Behaviour

Bounce Rate = # of email campaign visits with a single Pageviews / # of email campaign visits

Length of Visit = percent of email campaign visits that last longer than xx seconds

Business Outcomes

Conversion Rate = # Orders / # of email campaign Visits

Average Revenue per Email Sent = total revenue / # of emails sent

Email Campaign Profitability = (Revenue generated – campaign cost – cost of goods sold) / # of emails sent

Analytics – Retail Site KPI’s – Example

Retail Site Example – Key Performance Indicators

You can download this post here.

Level 1 KPI’s

Buyer Conversion Rate
–    Describes the likelihood that a person will turn into a customer
o    Total Customers Converted / All Visitors = Buyer Conversion Rate

Average Cost per conversion
–    Ensures that you’re not paying too much to acquire visitors.
o    Sum of Acquisition Marketing Costs / Total Conversion Events = Average Cost per Conversion

% High and Low Customer Satisfaction
–    Indicates how well your site serves your customers goals.
–    On exit surveys:
o    Did you find what you want? YES/NO
o    Net Promoter Score – Would you recommend us to a friend? YES/NO
–    Questionnaires

Level 2 KPIs

Ratio of new visitors to returning visitors
–    The ratio of the two gives you a single metric that effectively describes the particular “acquisition mode” exhibited by your web site.
o    Total New Visitors / Total Returning Visitors = Ratio of New to Repeat Visitors
o    This number will be around 1.0, Below 1 means you’re in the business of retaining visitors, above 1 means you’re acquiring new customers

New & returning visitor conversion rate
–    The conversion rate segmented by new and returning visitors to your site will help you understand how much consideration your offer requires.
–    Shows how you get your initial conversion rate
o    Total New Visitors Converted / All Visitors = New Visitors Conversion Rate
o    Total Returning Visitors Converted / All Visitors = Repeat Visitors Conversion Rate

Stickiness of Homepage and key landing pages
–    One of the most important marketing key performance indicators is page “stickiness” – the likelihood that your landing pages will keep people on your site.
o    100% – Bounce Rate = Page Stickiness

Level 3 KPIs

Check out completion rates
–    Given the importance of the checkout process, the checkout completion rate is among the most important ecommerce key performance indicators.
–    Total Orders / Total Visits where the Checkout Process is Started = Checkout

Completion Rate
Order conversion by Campaign type
–    Tracking your marketing campaigns through to conversion is among the most important and valuable uses for any web analytics applications.
–    Describes the likelihood that any individual visit, from a specific traffic source or campaign type, to your site will make a purchase.
–    Total Number of Orders Taken Campaign Type /  Total Visits from Campaign Type = Order Conversion Rate by campaign

% High/Medium/Low Time on Site
–    Categorizing your visitors in terms of the average time they spend interacting with your site will help you better understand the activities of different “interest” segments.
o    Interest segment = understanding levels of user interest (the less time visitors spend on site, the less interested they are and less likely they are to buy)
–    For most sites, a “low” amount of time spent is 30 seconds or less, a “medium” amount of time spent is between 30 seconds and five minutes and a “high” amount of time spent is more than five minutes.

% High/Medium/Low Click Depth
–    When diagnosing problems with conversion and revenue generation, one should keep the notion that all of this data is based on people generating clicks.
–    If too high a percentage of visitors to your site are clicking on too few pages it is extremely unlikely that they’ll convert. Especially when your definition of “low click depth” is fewer clicks than your checkout process requires.
–    This measurement can be a good gauge of the real volume of visits that were likely to convert in the first place.

Site Search Analytics

–    Each site has Search functionality. The performance and use of the site search facility can offer interesting insights into user goals and information needs.  Reviewing and optimising performance of search result pages can enhance the usability of the site.
–    Google Analytics can be configured to capture search data
–    Search KPIs would include

  • Search to purchase conversion rate: How influential is search in generating conversion
  • Percent zero results: How searches deliver no results i.e. no information relevant to search query
  • Zero yield searches: Amount of searches that don’t deliver a response from the user (the result page contains no relevant links)
  • Search refinements

 

Conversion Rate Optimisation – Website Traffic Analysis

Uncovering issues with you your website can help you identify issues that are preventing your visitors completing the tasks you want them to.  Through analysing your website traffic there are three main areas for concern – traffic sources, site content and site search analytics.

You can download this post here.

1.    Traffic Sources

a.    Direct

i.    Direct input of URL into browser driving traffic to homepage
ii.    Mainly the result of off-line marketing activities, event driven PR or brand strength
iii.    Generally if this s a significant amount of traffic, the Home pages should be de-cluttered and focused on conversion action as visitors are already aware and familiar with your company

b.    Referred

i.    In bound links – Can link to any page within your website
ii.    Review referrer links of major traffic source to understand context (positive/negative) – amend landing pages accordingly

c.    Search

i.    SEO can offer a free stream of traffic to your site but the landing page, whilst relevant to the keyword, may not be effective in supporting conversion goals
ii.    Landing pages should be reviewed to consider if they effectively transport incoming visitors from important keywords to intended conversion paths.

d.    Paid & Owned Media

i.    Paid Media: PPC, Display ads, 3rd Party emails
ii.    Owned Media: Newsletters, Renewal Emails, Social Media, RSS
iii.    Such traffic can be controlled (turned on/off, increased/decreased), targeted to  specific landing pages, and it’s value and profitability can be tracked (if configured correctly)
iv.    Traffic should be mapped against targeted landing pages and performance should be reviewed.
v.    Poorly performing pages should be candidates for testing, redesign or creation of campaign specific landing pages.

e.    Device

i.    Traffic from mobile devices increases everyday and should be reviewed
ii.    Mobile users will often behave differently from desktop users due to the context of the device
iii.    Mobile users should be served a site that’s appropriate for their needs

2.    Content

a.    Most Visited Content

i.    The popularity of a webpage helps you to understand if it’s getting the right exposure
ii.    If a key page is not getting enough traffic, it may be necessary to move it to a more prominent location or increase links to it from other popular pages

b.    Path Analysis

i.    Allows you to see the sequences of pages that visitors use to traverse your website
ii.    They show the most common flows of traffic
iii.    It may be possible to change the position of key conversion pages or links within the site to benefit from the drive-by visibility

c.    Top Entry Pages

i.    A list of the top entry pages shows you the point of first contact with your site.
ii.    Generally, the more traffic that is hitting a landing page, the more attention that page deserves in terms of conversion tuning.
iii.    Traffic levels can help you to prioritise which landing pages need to be fixed first

d.    Top Exit Pages

i.    Exit pages are were visitors leave your site – they probably did not find what they were looking for
ii.    These pages should be reviewed for improvement by providing more relevant information or better navigation
iii.    The total number of exits and exit percentage of a page can be used to prioritise among problem pages
iv.    High bounce rates on high traffic pages are high priority pages

e.    Funnel Analysis

i.    In order for conversion to happen on ecommerce sites, visitors must pass through a well-defined series of pages to convert
ii.    The funnel narrows as people drop during each step – high drop-off rates may signal that a particular page is especially problematic.

f.    Conversion Goals

i.    Google Analytics must be configured to measure all your important conversion goals (Check Out Entry, Check Out Completion, Page Shares, Facebook page visits)
ii.    Reverse goal path analysis can show the most common sequences of pages that visitors traversed on their way to completing goals – revealing the most popular points of origin for a conversion.
iii.    In-page analytics overlays data on top of the clickable links on a webpage.  This analysis can suggest improvements in the organisation of information on a landing page

3.    Site Search Analysis

a.    Site search can be used to aid conversion and help visitors find relevant information

b.    Many users will abandon a site if they do not find what they are looking for on the first page of results

c.    Many searches produce no matching results, indicating a mismatch between visitor desires and expectation, and the ability of a site to provide relevant content

d.    Site Search Analysis can help you optimise search to enhance the user experience and gain valuable insights into what you customers want

Coversion Rate Optimisation (CRO) – Tuning Elements

Once you’ve identified landing pages to optimise you need a plan of action.  Generally speaking there are a few common testing themes and a number of testing elements to choose from.

They’re detailed below. But you can download this all here.

Testing Themes

1.    Tuning Multiple-Page Flows

a.    Tuning Check out page flows in order to reduce check out abandonment and increase conversion rate

2.    Less is More
a.    This is an exercise in editing – Instead of creating alternatives to the original page’s element, you should consider doing away with them completely

b.    This theme can be applied to a whole range of testing elements:

  • Fewer & smaller graphics
  • Shorter bulleted text
  • Reduced number of choices and links

3.    Personalisation

a.    Personalisation can be used to build desire and affinity for your particular solutions.

b.    It can be tested using a wide array of available tactics:

  • Present localised content by using geo-targeting information
  • Show last-minute special offers via exit pop-ups to visitors who are about to leave your site without converting
  • Follow up by phone or e-mail if someone abandons your registration process partway
  • Customise content by visitor role once someone has self-selected

4.    Test the offer

a.    Ultimately, it is your offer that gets people to act.  However, when considering specific elements there are lots of ways you can influence someone:

  • The primary offer
  • Headline, Sales Copy, Images chosen, Formatting
  • Repetition of CTA in multiple screen locations and formats
  • Limited availability or scarceness indicators

5.    Price Testing

a.    Discount vouchers

b.    Volume discounts

Selecting Elements to Tune

1.    Page Structure

a.    Page structure defines how the real estate on your page is organised and used.

b.    Typical page structure testing elements include:

  • Size and content of page header
  • Size and content of page footer
  • Size and location of page navigation
  • Placement of trust symbols and credibility logos
  • Separation of page shell and navigation from page content
  • Size and location of forms or other CTAs
  • Single versus multiple columns

2.    Information Architecture

a.    Information Architecture defines the way that information is organised on your site

b.    Typical IA related test elements include:

  • Self-selecting by role or by task
  • Clear and distinct descriptive link text and choices
  • Sensible and prominent page titles
  • Breadcrumbs or other context
  • Consistent placement of all page elements
  • Navigation
  • Number of available choices presented
  • Alternative navigation methods
  • Cross-linking to other key information
  • Availability and format of onsite search
  • Error correction

3.    Presentation

a.    This mainly has to do with format in which you deliver your message

  • Degree of detail (e.g. full text, text expansion  or links to supporting info)
  • Writing format (inverted pyramid vs traditional pros)
  • Choice of input elements (e.g. Radio Buttons, Pull downs)
  • Action Format (e.g. buttons, test links, both)
  • Editorial tone of your writing
  • Use of alternative formats or modalities (e.g. charts, figures, audio clips, video, presentations, demos)

4.    Emphasis

a.    Emphasis is about the relative importance you place on something

b.    Try to selectively focus attention on the key elements on your page, and de-emphasise everything else:

  • Amount of screen real estate devoted to an item
  • Use of relevant images (e.g. specific products or believable people)
  • Image captions
  • Font sizes and font families (e.g. Headline sizes)
  • Font emphasis e.g. italics, bold, background colours)
  • Background colour blocks or background images
  • CTA Buttons shapes, sizes, visual styles and effects (e.g. bevelling, borders, drop shadow)
  • Visual separators (e.g. horizontal rules)
  • Use of white space and visual isolation to focus on important items
  • Removal of distracting secondary information