Optimizing Search to Enhance the Digital Customer Experience · Optimizing Search to Enhance the...

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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



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.



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).



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.



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).



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.



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.



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.



“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?”



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.



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.



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”)



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.



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.



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.



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.



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.



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,



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.



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

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