Growth Hacking Tactics

The following notes were taken from reading Growth Hacking: A how to guide on becoming a Growth Hacker by Jose and Joe Casanova.

Strip down your home page to the bare essentials

–          Design your website with a minimalist approach

–          Most people wont find you through your home page – rather another landing page from a shared link or natural SERPs

–          Users will more than likely visit your home page to learn more about you so don’t distract them from this mission otherwise they may just leave

–          Notable companies who stripped down there home page include Facebook, Twitter, Quora, Groupon

Integrate your product with a business that has a large user base

–          Spotify became one of the first companies to integrate its product into Facebook’s newsfeed

–          Paypal integrated into eBay

–          Zynga integrating with Facebook

Speed up your website

–          People wont hang around for pages to load

–          Go to a public library and test how long a webpage takes to download

–          Resource intensive page elements like video or flash objects can affect speed

–          Fast page loads = high satisfaction

Social Proof

–          Users value others  opinions and advice when making decisions

–          This can be demonstrated through customer testimonials, logo’s of established companies, customer statistics, thought leaders

Growth Hacking Strategy

The following notes were taken from reading Growth Hacking: A how to guide on becoming a Growth Hacker by Jose and Joe Casanova.

A growth hacker’s goal is to leverages different fields of expertise to move users along a predetermined “user experience funnel”.

Funnels differ, but a common flow is:

> Hears about your product

> Visits your website

> Creates an account

> Refers a friend

> Pays you

To accomplish this GH build in scalable marketing features in a product and ensure that every aspect of the user’s experience is custom-tailored to lead them to the next step in the funnel.

Content marketing, social media marketing, virality, product features that encourage sharing and involvement are all examples of new marketing ways to cut through the deluge marketing noise.

The Growth Hacking Funnel

AARRR – Dave McClure (Startup Metrics for Pirates)

Acquisition, Activation, Retention, Referral, Revenue

Stage / Example

Acquisition / Use a/b testing to engineer landing pages optimised to generate more  sign-ups

Activation / Earn users trust by providing high-quality content to consumers in your niche. Leverage SEO to get the most out of your content marketing efforts.

Retention / Evaluate how consumers use your product, experiment, and recreate until you find a strategy that attracts and retains long-term growth.

Referral / Provide tools to enable users to share content easily (addthis, sharethis, prompting)

Revenue / This is dependent on the business model.  However, if you’ve worked hard enough at the first four stages the final stage should feed itself.

Growth Hacking Strategy

Growth Hacking strategy is based around 4 main questions:

  • How do I get more people to sign-up?
  • How can I get new users activated as quickly as possible?
  • How can I best engage and retain my users?
  • How can I bring back customers who have fallen off the platform?

 

Growth Hacking

The following notes were taken from reading Growth Hacking: A how to guide on becoming a Growth Hacker by Jose and Joe Casanova.

What is it?

The majority of online businesses focus on retention and engagement.

The more engaged users are the more likely they are to refer friends, family and professional contacts.

This drives organic retention, as a larger base will increase engagement and referrals.

This concept is known as virality (word of mouth in old money).

Growth Hacking is a data-driven outgrowth of marketing and product development disciplines.

It’s about getting people to keep using a product once they’ve tried it and how to get them to tell their friends and family about it.

The main objective of GH is the same as all business – growth.

Growth must be the central goal of the product for GH to work.

Growth is something that business people understand but “hacking” is a little more unfamiliar.

Hacking simply means to find a simple solution for something (check life hackers for examples of creative solutions to life’s everyday problems).

In the marketing context, hacks are the solution to sustained growth.

Traditional marketing sells an existing product; growth hacking creates a product that will market itself.

Growth Hacking Example

Twitter realised that users who followed at least 5 other users when opening a new account were more likely to return and use Twitter again.

Twitter put in place projects to ensure that all new visitors had to do this when opening an account.

Behavioural Economics – 6 key principles of influence by Robert Cialdini

These key principles are detailed on wikipedia.

  1. Reciprocity – People tend to return a favor, thus the pervasiveness of free samples in marketing. In his conferences, he often uses the example of Ethiopia providing thousands of dollars in humanitarian aid to Mexico just after the 1985 earthquake, despite Ethiopia suffering from a crippling famine and civil war at the time. Ethiopia had been reciprocating for the diplomatic support Mexico provided when Italy invaded Ethiopia in 1935. The good cop/bad cop strategy is also based on this principle.
  2. Commitment and Consistency – If people commit, orally or in writing, to an idea or goal, they are more likely to honor that commitment because of establishing that idea or goal as being congruent with their self-image. Even if the original incentive or motivation is removed after they have already agreed, they will continue to honor the agreement. Cialdini notes Chinese brainwashing on American prisoners of war to rewrite their self-image and gain automatic unenforced compliance. See cognitive dissonance.
  3. Social Proof – People will do things that they see other people are doing. For example, in one experiment, one or more confederates would look up into the sky; bystanders would then look up into the sky to see what they were seeing. At one point this experiment aborted, as so many people were looking up that they stopped traffic. See conformity, and the Asch conformity experiments.
  4. Authority – People will tend to obey authority figures, even if they are asked to perform objectionable acts. Cialdini cites incidents such as the Milgram experiments in the early 1960s and the My Lai massacre.
  5. Liking – People are easily persuaded by other people that they like. Cialdini cites the marketing of Tupperware in what might now be called viral marketing. People were more likely to buy if they liked the person selling it to them. Some of the many biases favoring more attractive people are discussed. See physical attractiveness stereotype.
  6. Scarcity – Perceived scarcity will generate demand. For example, saying offers are available for a “limited time only” encourages sales.

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.