Post on 05-Jul-2020
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Optimizing Search to Enhance the Digital Customer Experience
Best practices for search: From initial query to final results
Searching the World Wide Web has become an integral part of our
culture. People rely on the Internet for information about nearly
everything, from hours and directions to their favorite stores, to
information about diseases and treatments, or comparing prices and
buying their favorite products.
Content has exploded in both depth and breadth, and is now presented in
many formats, including text, images, and video. The Internet has gone
way beyond an index of static pages of text, to include all forms of media
Optimizing Search to Enhance the Digital Customer Experience
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and dynamic Web pages that are constantly changing, some even on the
fly as a result of actions by the users themselves.
Furthermore, users are searching not only from their computers at home,
but from mobile devices as well. This emergent paradigm has changed
the way Google and other major Web search engines handle both the
growing volume of indexed content and the increasing number of
searches being conducted.
All of these developments have added up to a need for greater
sophistication in search capabilities at every step of the search process. A
typical online search experience begins with a search of the Web to find a
page of interest, then shifts to a search of the website. Finally, the user is
shown a set of results, and the results can vary in how they are presented
and what can be done with them.
From an ecommerce perspective, search is an essential ingredient in the
digital marketing formula for attracting visitors and converting them to
customers. This white paper provides insights on the impact of search on
each stage of the customer journey. It examines the customer experience
as it transitions from Web search to site search and makes
recommendations about best practices to enhance the user experience
and improve the customer journey from awareness to purchase.
Optimizing Search to Enhance the Digital Customer Experience
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Searching the Web
To stay competitive and even relevant, companies must pay careful
attention to how the popular search engines are indexing and ranking
pages for any given keywords, in particular, those most closely tied to
their business or site. This section of the white paper will cover the basics
of search engine optimization (SEO) practice as well as touching on some
recent developments, to allow our readers to formulate strategies that
best meet the needs of their business.
Since the majority of searchers don’t click past the first two results pages,
getting a good ranking is more important than ever. The basic tenet of
Web search is that if a search keyword matches one or more of the
primary elements of a webpage, that page will likely be ranked higher
than others. These elements are usually the URL and H1 HTML tag or
other prominent headers.
Best practices for SEO should include a blend of tried and true common
practices and a keen awareness of analytics data, new developments in
technology, and the ranking of website pages. Much has been written on
SEO, as good SEO produces dollars. Other common practices include
search engine marketing (SEM), and pay per click (PPC).
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These search marketing strategies, while primarily focused on generating
revenue, have well-developed techniques to capture user queries and
persuade the user to choose a particular site from the search results.
SEO, SEM, and PPC use similar techniques to ensure that their pages
indexed well enough to be at the top of search results pages for specific
user queries. These practices have included both ethical and not so
ethical means of forcing sites to the top of search results pages, also
known as SERPs.
Traditionally called White Hat versus Black Hat SEO, the approaches
differ primarily in whether the customary means of boosting a pages rank
in search results have been adhered to, thus producing a set of results
that are actually relevant to the user. Forcing anything and everything on
users by way of propped up pages and artificial means is actually
detrimental to a page’s trustworthiness and ranking as a result. The Black
Hat practices of SEO have been recognized by the major search engines
and can cause a site or pages to be permanently banned from a search
engine altogether.
In today’s world of billions of web pages and aggressive Internet search
marketing techniques, quantity and quality also play a very significant
role. The quality of a page is judged by its unique content and number of
other sites that link to it. The quantity of keywords and content can also
affect page rank, but Google and other search engines have become
sharp at evaluating quality of pages and weeding out results that are
based solely on quantity for quantity’s sake, such as the Black Hat SEO
technique of keyword stuffing. In this practice, a particular keyword is put
on the webpage multiple times, in order to increase the chances of the
page being ranked as relevant. Cloaking is another Black Hat technique,
in which the keywords, titles, or descriptions of the web pages do not
match the content. Link farms boost rankings by creating a set of
interconnected websites that artificially increase the number of links to the
company’s page. Finally, pages can be created that have a high ranking
but then redirect the user to another page.
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Search engines are becoming progressively smarter at indexing the best
bona fide content and providing users with the best possible curated lists
of search results, almost to the point of mind reading. The ability of
Google and other search engines to auto-suggest, remember repeated
searches, and even curate results based on search history and user
location are further customizing the user experience and raising people’s
expectations of Web search.
Tools such as Google Adwords can provide quantity of searches on
specific terms by month, year, or over any time period to help guide the
design of specific pages. Users typically trust organic search results
more than paid search results, so getting your company’s page(s) to
show up naturally in a search is far better than placing them there
artificially with a technique in which a site or pages pays for the top spot
in a given search engine. By far the best way to organically boost
rankings is to use common terms prominently in the URL and header tags
of the page, while curating the best unique content on the page and
increasing the number of links to your page(s).
Meta-keywords, or keywords embedded in the page as tags, don’t hold as
much weight as they once did before the explosion of content and
competing pages for search engine attention. Be sure to follow best
practices and provide the user with unique enriching content to achieve
high rankings. During the building of site pages, common vernacular and
most-used terms must be considered in order to provide the best possible
findability in Web search.
Most search engine indexing and ranking techniques are proprietary and
considered trade secrets, but with a little bit of reverse engineering it’s
easy to understand the basics of Web search and apply them to your
company’s initiatives. Web search engines index millions of Web pages
every day, with new pages getting their official spot after a month or so.
Having durable, unchanging URLs is critical in increasing page rank, as
search engines do not respond well to redirects or changing URLs.
Some practices can sometimes be deemed as untrustworthy and can
significantly damage a page’s ranking if they become classified as Black
BY FAR THE BEST
WAY TO
ORGANICALLY
BOOST RANKINGS IS
TO USE COMMON
TERMS
PROMINENTLY IN
THE URL AND
HEADER TAGS OF
THE PAGE, WHILE
CURATING THE BEST
UNIQUE CONTENT
ON THE PAGE AND
INCREASING THE
NUMBER OF LINKS
TO YOUR PAGE(S).
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Hat SEO practices. For example, a page might attain a certain rank on
one set of keywords, but then change its name and/or content to push
something different from what the user actually searched for. If the page
has keywords in multiple places and this cannot be avoided, use special
devices such as canonical tags to let the Web crawlers know you are not
trying to prop anything up artificially. The tags will cause the Web
crawlers to ignore the multiple instances of the keywords where
applicable. In addition, users do not like ending up on a page that does
not match their needs.
While Google and other search engines are generally honest about their
indexing and search results, in many cases popularity will ultimately
decide which pages are ranked first for a given keyword, and thus the
process becomes subjective and user defined. Providing unbiased
balanced search results is almost an impossibility in today’s world, given
the volume content, so when all other tie breakers are exhausted and
pages still seem to appear relevant, the most popular page wins. Of
course it may or may not be the best page, but Google and other search
engines take this gamble, especially considering that it’s all about money.
Traffic is worth its weight in gold, and ultimately the more traffic Google
and other search engines can get, the more they can charge for
advertising space and PPC.
Typically, matching keywords to prominent page features such as page
URL and header tags should produce results, but that is not always the
case. It’s quite possible that once a user gets to a highly ranked page,
spending time on the page will also affect that page’s ranking. Popularity
is highly influenced by back linking, i.e., how many other sites link to the
site, but site traffic also plays a major role.
Some sites use a blended method of ethical and not so ethical
techniques, sometimes referred to as Gray Hat SEO, that furthers distorts
the reverse engineering process and adds more mystery to finer aspects
of SEO. Keyword stuffing is probably the most common Black Hat
technique to be used in conjunction with legitimate ones, because it is
relatively easy to do. These Gray Hat SEO techniques may be rooted in
PROVIDING
UNBIASED
BALANCED SEARCH
RESULTS IS ALMOST
AN IMPOSSIBILITY IN
TODAY’S WORLD,
GIVEN THE VOLUME
CONTENT, SO WHEN
ALL OTHER TIE
BREAKERS ARE
EXHAUSTED AND
PAGES STILL SEEM
TO APPEAR
RELEVANT, THE
MOST POPULAR
PAGE WINS.
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the best intentions, but will likely backfire and result in more harm than
good for your pages.
Other factors that influence how search engines index and rank individual
pages and sites for specific keywords include more mechanical aspects
such as site architecture, page structure, and URL structure. Well-
designed sites with clean URLs will often rank better, as will sites without
HTML code bloat and too much Flash or other media content.
A further dimension to Web search has been introduced in the modern
paradigm called personalized search and contextualization. Not only are
search results being populated based on basic ranking factors and
matches, but are further refined based on the user’s search history,
preferences, and even location. This deeper level of mind reading, while
sometimes bordering on “digital creepiness,” is further enhancing the
process for users while complicating the process for website builders.
More personalized sites and even dynamic sites must be created to
capture all forms of user search queries, from the basic to the complex,
the general to the very specific. This coupled with additional media
content points to the need for paying strict attention to site structure and
architecture, in addition to keyword matching and where appropriate and
needed, meta-keywords.
The multi-channel multi-platform, multi-device environment that is
emerging is creating a more contextualized personalized search
experience, as Forrester has noted in its research. Semantic
contextualization is paving the way for more individualized search
experiences. Search needs to anticipate what people need, and go
THIS DEEPER LEVEL
OF MIND READING,
WHILE SOMETIMES
BORDERING ON
“DIGITAL
CREEPINESS,” IS
FURTHER
ENHANCING THE
PROCESS FOR
USERS WHILE
COMPLICATING THE
PROCESS FOR
WEBSITE BUILDERS.
“CIOs: The Web’s Golden Age Is Ending” For years, we've functioned under the expectation that no one controls the Web. But as the Web splinters into the new age of the "Splinternet," companies, not standards bodies, rule interactive elements. The days of standardized web-established links, click-throughs, and analytics are over.
-- Sharyn Leaver, Josh Bernoff, Shar VanBoskirk. Forrester Research, 2011.
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beyond just the basics of matching keywords to URLs and H1 tags of
popular sites. The idea that no one controls the Web and it’s an equal
opportunity field is being challenged in an era of “companies ruling
interactive elements,” as Forrester reports.
All things considered, the best approach to tackling Web search will be a
reliance on SEO best practices, while not being naïve and ignoring the
increasing amount of proprietary techniques and niche markets. There is
really no way to outsmart Google or other search engines. The best
approach is to leverage their capabilities to connect the user to what you
are presenting.
Site search
Once the user reaches a target website, the challenge remains to find the
exact information that is needed. Much like SEO, site search has
undergone major improvements and innovations since the early days of
the Web, and this section will address some of the highlights and how to
leverage them. However, the main caveat here is that site search is
internal, i.e., searching on a site not searching the open Web. This
internal content is structured and purposed very differently from the web
pages themselves.
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“Why can’t it be just like Google?” is a common complaint about site
search, and in order to understand why it can’t be like Google one needs
to understand this basic principle. Because the user is not searching an
index of billions of web pages that are mostly ranked based on popularity
and also may include paid results ranking, the approach to site search
needs to be different. Today’s site search must be able to search multiple
formats, such as text, forms, images, and video, and to anticipate users’
needs instantaneously, with advances such as type-ahead/auto-complete
and auto-suggest.
One factor that strongly influences site search strategy is that content on
websites is no longer structured and stored in on centralized location.
Organizations are aggregating all of their content and data and making it
searchable from one interface, but they are using multiple repositories.
Major site search software and Web search platform providers such as
Endeca have made this possible. Catalog items, reviews, articles, media
content, and their metadata are being indexed by search platforms and
made searchable by intelligent search modules and key value pairs.
The site search box
has developed the
ability to anticipate
what users is looking
for, and even suggest
some things they may
not have thought of
previously. In addition
to having the ability to
auto-correct
misspellings and other
typos, the search box can suggest terms that can be pulled from
controlled or uncontrolled lists. These lists, which include items such as
brands, categories, products, articles, or other custom content, and top
searches, should be curated to provide the best and most streamlined
user experience. Suggesting multiple forms of a term or a misspelled
“WHY CAN’T IT BE
JUST LIKE
GOOGLE?”
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version of the term in type-ahead does not provide an efficient means for
users to get to what they are looking for. The search function should do
the work of anticipating the user’s needs and respond accordingly.
In addition to providing users with custom curated results before they
even perform a search, the query process and search results have also
undergone major fine tuning. A number of algorithms can be employed to
ensure the best possible free-form search results. When organic search
results are not sufficient, hard redirects can be employed to instantly take
the user to a specific landing page for any specific term(s). Furthermore,
search engines can be helped along by the creation of a thesaurus of
terms that can be linked as equal to the term or as subsets of one
another. For example, if the user searches for either “California” or “CA”
results for both can be presented separately, or the combined results can
be presented as “California” for a more streamlined experience. These
decisions will depend heavily on what content is being searched, and the
desired user experience.
Some other common tools used to refine the modern search include stop words, freshness boost, term proximity, minimum match or match mode, field weighting and relevance ranking, and content type boosting. Each of these is described below.
Stop words
Stop words are words that are ignored by the search engine. Commonly
occurring terms such as “the,” “as,” “in,” and “of” that cause problems
when searching for phrases that contain them are automatically removed
from any search queries. These are also called “noise” because they do
not add to the value of the search. These terms can be user defined
[aren’t they normally identified prior to the user conducting the search?]
and removed from the search index as well as being ignored altogether
by the search engine in user queries, regardless of the index.
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Freshness boost (a.k.a boost and bury) and content type boosting term proximity
Freshness boost refers to boosting results to the top of the search results
set based on the date of origination of the document. Depending on the
context, users may want to see newer documents over older documents,
all things being equal.
Content type boosting, similar to freshness boost, returns specific content
types above others based on relevance. Certain documents should be
boosted by the search algorithm based on content type, as they’re more
likely to be relevant for users. For example, in a Google search, web
pages are ranked over photos.
Minimum match or match mode
The minimum match tool provides much more control than a simple
Boolean AND vs OR rule. Solr, an open source search engine from
Lucidworks, allows developers to define the number or percentage of
terms for a given query that need to appear in a document for it to be
considered relevant (e.g., if three or fewer terms are used in the query, all
must match terms in the document; if four or more search terms are used,
then at least 75% must match terms in the document).This technique is
also called “match mode” in Endeca; the greater number of matched
terms, the better the ranking in the results. For example, “max partial
match” matches the maximum number of terms first, and then ranks the
remaining results based on number of terms matched.
Field weighting and term proximity
The developer can define matches in the title or header field as more
relevant than matches within the body of a document. Matches in specific
fields can also be given more weight than matches in other fields (called
field ranking), and further ranked on how they matched (called relevance
ranking). Term proximity refers to higher ranking of results based on how
close to each other the search terms appear.
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In multi-term queries, the closer the terms appear to each other, the more
likely the document is to be relevant. Developers can define how close
the terms must be to each other in order to be considered relevant. Field
weighting can also be designed as a module within type-ahead, ranking
suggested queries higher that have the terms closer together in the string.
In addition to incorporating these back-end configuration tools, modern
site search goes beyond the search box and the results set. In addition to
anticipating what the user is looking for with type-ahead and advanced
algorithms, search solutions have added faceted search, also known as
parametric search, to the use of type-ahead and advanced algorithms.
Any number of attributes and metadata fields can be applied to the
records to narrow a user’s search results according to whatever factors
are considered relevant. These can be category, brand, price, rating, or
attributes such as format, author, and subject in a more traditional library
setting. Not only can results be filtered by any number of refinement
types, but the metadata can also be used to drive a comparison view of
search results, with records displayed
side by side. This technique allows the
user to instantly compare different
selected search results side by side.
Also being addressed automatically in
the modern site search experience are
misspellings and null searches. In
addition to using thesaurus entries and
redirects within the search engine to
manually catch these otherwise empty
search results, many search engines
have the ability to auto-correct and
approximate misspelled queries and
other terms that would otherwise provide
no results. Simple misspellings and
typos like “giutar” and “chmes” are
autocorrected (as “guitar” and “chimes”)
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and then the correct term is queried and results provided. If the term is
too unrecognizable, a “Did you mean?” option can also be enabled to give
the power of correction to the user to select the correct search term.
These advanced tools prevent dead ends within the user experience,
keeping the user engaged and searching on the site.
Search Logs and Analytics
A very critical aspect of site search that often gets neglected in the face of
user experience design and algorithmic fine tuning is search logs and
analytics. To successfully implement any or all of these tools, one must
first consult their site search logs and analytics data to find out what
people are searching for, how they are searching for it, and what actions
they are performing as a result. For example, are they leaving the page
after searching on a specific term? Or are they clicking through to
checkout? Are they clicking on site map or related category links
indicating they haven’t found what they are looking for but have not gotten
to the point of giving up? Are they clicking on chat to ask for help after
searching? Web analytics are critical for understanding the user’s intent
and outcomes.
In addition, search logs provide the top searched terms and insight into
the users’ vernacular, thus enabling fine tuning of search algorithm(s) and
the addition of appropriate thesaurus entries and redirects. Once the
redirects are in place, comparisons can be made of how redirected
search performs against organic search. A/B testing can also be used to
compare them in real time.
In conclusion, search platforms are becoming increasingly intelligent and
more able to anticipate the user needs and personalize the experience.
Contextualization and personalization are the wave of the future of
search, and must be leveraged and integrated to the fullest extent
possible.
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Presenting Search Results
The final step in the process is to present the user with a search results
page (SERP). Search results presentation has gone far beyond the
traditional free-text abstract view highlighting the matched keywords and
where they matched. This style of presentation is very limited and often
results in too much “noise” for the user to sort through, matching on
keywords in too many places and often providing “false drops,” or results
not relevant to the searcher. In addition, with so much text being
presented in free form, refine-ability is limited. The presentation of object
abstracts requires the user to manually sort and sift through a lot of text.
In some cases, users simply abandon their search.
Textual forms of search results presentation are still in use, but mostly in
academic and research settings, where the primary asset of each object
is its text. For these SERPs, the most common presentation is a list of
abstracts that show the matching keywords highlighted or in bold. This
presentation allows the user to see exactly how and where their query
matched, and make a decision about whether the result is of interest,
based on the matching.
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Results are also sometimes sorted based on proximity matching, i.e., how
close together the matched terms are to each other, or other relevance-
ranking modules. However, this approach is becoming outdated, as
users now expect much more refine-ability and deeper attributes such as
thumbnail images or logos, as well as related items/categories/links.
Currently, SERPs are able to provide deep customization and refine-
ability. Users can filter results by any specified metadata field associated
with the results records in the database, such as category, brand, rating,
price, or more specific attributes such as size, color, weight, and material.
This ability has enabled users to customize their own search pages,
helping them get to results they are seeking more quickly than ever.
Typically, these refinement attributes are presented in the left navigation
pane of a SERP, but also can be leveraged to drive what is called
“compare functionality,” which is discussed below.
In order to keep users from abandoning their search, more recent search
results presentation methods have streamlined the experience with the
power to customize and personalize. In the following sections, we
discuss some of these advances.
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Compare functionality
Compare functionality is the ability to select two or more items from a
search results and view them side by side, comparing any specified
metadata or attributes. This technique is very helpful when the user
wants to see specific differences between
results in the set, and size up similar products.
For example, in a search for guitars, the user
might be comparing sizes, number of strings,
body material, and price of two selected
guitars from a search results page. Armed
with this information, the user is more able to
make an informed decision about the
purchase. This tool is very valuable, enabling
users to further deepen their search by
selecting only those results which are of most
interest to them and comparing their
specifications. From the merchant’s
perspective, the compare functionality enables
ecommerce sites to more closely replicate the
in-store experience.
Refinement Types
Further refinement and contextualization can be achieved by filtering
results within the user’s preferences as indicated by geographic location,
browsing history, and purchase history. This deeper personalization is
paving the way for a more specialized experience, further enabling sites
and search engines to anticipate what users need, and get them to it
more quickly. Also becoming ubiquitous on site search results pages is
results clustering based on the user’s settings and search history. Not
only are results refined and filtered, but they are organized and sorted
based on relevance to both the query and to the user’s specific
preferences and history. For example, on Linkedin.com, a people search
will list people in the user’s network first.
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View Options
In addition to refinement and compare tools that allow the user to view
and compare attributes of particular items, other tools are available to the
user, such as list view and grid view options. Listing search results gives
the user the ability to compare more detail of each item, such as title and
an abstract of the description. This is the search results presentation
most widely used by the major web search engines. Grid view is more
common in ecommerce sites, as it allows the user to see more results per
page and scan the thumbnails and product name of each item quickly.
Each view has its pros and cons, so it is best to test them on your site to
find out which is engaging the user more.
Sorting
In addition to attribute/metadata refinement ability on SERPs, the other
major tool available to the modern searcher is sorting. Similar to attribute
refinements, the search results sort feature allows the user to order
results based on any specified metadata field, including price, rating,
best-selling, or product name in alphabetical order. This is another
powerful tool that gives users the ability to customize their experience and
access the desired information more quickly and efficiently.
Pagination
Pagination is another area of search results presentation that can be
placed in the hands of the user. Finding a balance between quality and
quantity is paramount. Ideally users will see enough results to keep them
interested without overwhelming them with too many. Fortunately,
today’s SERP pagination allows the user to customize. Users are given
the ability to show segments of the search results in specific
denominations, or to show all search results if desired. This further
customization of the SERP gives the user additional power to view and
sort search results. A default can be established that is most common
among your users; however, the ability to change pagination should
always be present.
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Mapping search results
Another development that helps users personalize their experience is to
present search results on a map. This approach is very common, and
particularly useful for tools such as store locator, and on sites like
Craigslist where the geographic location is very relevant to the user.
Further personalization can be attained if users specify their location
before searching, or allowing the site to identify the user’s location, and
then include it when presenting the results. Results are then shown on a
map, sometimes with the distance to each from the user’s location.
Null Searches
Thus far we have discussed what is available to the user when entering a
search query that produces successful results. Equally as important, if
not more important, is what happens when the user places an
unsuccessful search query. Also known as “null searches,” an
unsuccessful search presents a dangerous moment in the user
experience, because at that point the user is likely to leave the page, or
“bounce.” In order to keep the user on the page and engaged, several
developments have been made to continue to guide the user and prevent
them from abandoning their search.
The “did you mean” feature is one we are all familiar with on Google. Any
misspelled terms or odd forms of terms are automatically corrected and a
search is performed on the correct or common term. A follow up search
may also be suggested on the correct spelling and/or common form of the
term(s). This feature is also becoming increasingly common on site
search pages, and is critical to keeping the user engaged and searching
on the page. The last thing any organization wants are frustrated users,
who will then go elsewhere to find what they need.
Desktop versus Mobile Presentation
A major caveat with implementing any or all of these features is the
fundamental difference between desktop and mobile device search
results presentation. Since the mobile experience shows a much smaller
set of results and a more limited view, in comparison to the desktop view,
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it is critical to test and evaluate any SERP features implemented in both
environments to ensure a seamless experience. Most modern SERP
features are scalable for both desktop and mobile versions of your site,
but it is very important not to assume the presentation will function and
behave properly on both. Careful implementation and testing are
necessary to ensure the best leveraging of these features.
Best Practices Depend on the Situation
All things considered, there is still no one “best practice” for search results
presentation. Grid view versus list view, text versus thumbnails, sorting
versus filtering, and pagination all have their place and importance to the
user. Best practice for a given site depends heavily on both the content
and the target audience. The presentation method should be vetted using
testing, in particular A/B multivariate testing. Monitoring user behavior
through analytics data such as click-through rate, conversion rate, and
bounce rate will help to determine what SERP presentation tools should
be implemented and how they should be configured. In addition, usability
testing and user surveys can be leveraged to get relevant feedback.
Careful attention must be paid to the differences between the desktop
and mobile environments so that users will have a positive experience on
any device. In most cases, a blended approach of presentation
techniques works best, providing users with the greatest number of
options to enhance their search. This approach provides the greatest
likelihood that users will find what they are looking for, or at least ensures
they find something relevant.
Conclusion
The search process is a journey that begins with a search of the Web,
moves to a specific site, continues with a variety of search strategies on
the site, and produces a set of results. The user should have a variety of
options for interacting with these results, including sorting, filtering, and
comparing functionality. The user’s experience along with way has a big
influence on whether the ultimate transaction is completed successfully,
whether that is finding needed information or completing a purchase. The
BLENDED
APPROACH
PROVIDES THE
GREATEST
LIKELIHOOD THAT
USERS WILL FIND
WHAT THEY ARE
LOOKING FOR, OR
AT LEAST ENSURES
THEY FIND
SOMETHING
RELEVANT.
Optimizing Search to Enhance the Digital Customer Experience
Earley Information Science, Inc. All Rights Reserved. 20
experience is determined by multiple factors, including whether the site’s
SEO draws the user to that site, whether the search function on the site is
effective, and how well the results are presented. All of these in turn rely
heavily on data architecture and whether it provides the underlying
information for a successful search. Without this structure, no phase of
the search process can support the goal of meeting the user’s needs.
About Us Earley Information Science (EIS) helps organizations harness the value of one of their most important assets – information. We improve enterprise information agility to drive digital commerce innovation, increase revenue, and enhance customer experience with a strong enterprise information architecture and management foundation. EIS helps make information more findable, valuable and useable — thereby helping organizations improve operational efficiency and effectiveness. EIS has over 20 years of experience in working with Fortune 1000 organizations globally across many industries, including manufacturing, retail, financial services, healthcare, life sciences, the public sector, and professional services.
Earley Information Science PO Box 292
Carlisle, MA 01741 P: 781-444-0287 www.earley.com