The Complete Guide to Embedded Analytics

THE COMPLETE GUIDE TO

EMBEDDED ANALYTICS

http://www.logianalytics.com/

1

Table of Contents

Introduction.....................................................................................................................2

Part One: What is Embedded Analytics?.................................................................3

Part Two: Why is Embedded Analytics So Hot Right Now?.................................8

Part Three: Ways to Approach Embedded Analytics..........................................14

Part Four: Common Features in Embedded Analytics.........................................21

Part Five: The Business Case for Embedded Analytics.....................................26

Part Six: How to Be Successful with Embedded Analytics...............................40

Part Seven: Buying an Embedded Analytics Solutio...........................................52

Part Eight: The Future of Embedded Analytics....................................................60

Part Nine: Logi Analytics’ Approach to Embedded Analytics...........................63

Conclusion......................................................................................................................65



https://www.facebook.com/sharer/sharer.php?u=http://bit.ly/1gKbxgT

LinkedIn: http://www.linkedin.com/shareArticle?mini=true&url=http://bit.ly/1gKbxgT&title=The%20Complete%20Guide%20to%20Embedded%20Analytics%20-%20Logi%20Analytics&source=Logi%20Analytics&summary=Everything%20you%20wanted%20to%20know%20and%20more%20about%20embedded%20analytics!%201)%20What is embedded analytics%20and%20why%20is%20it%20so%20hot%20right%20now?%202)%20The%20four%20stages%20of%20embedded%20analytics%203)%20How%20to%20build%20a%20business%20case%20for%20your%20company%204)%20How%20to%20be%20successful%20with%20embedded%20analytics,%20and%205)%20The%20future%20of%20embedded%20analytics.&source=PDF

https://twitter.com/intent/tweet?text=Fantastic%20read!%20The%20Complete%20Guide%20to%20Embedded%20Analytics%20from%20@LogiAnalytics%20-%20great%20info%20for%20ISVs%20and%20SaaS%20http://bit.ly/1gKbxgT&hashtags=CG2EA

https://plus.google.com/share?url=http://bit.ly/1gKbxgT&hl=en-US

Introduction

Why Should I Read This?Every software company has one thing in common: the desire to create great products. But many software providers fail to leverage the full value of the data collected in their applications to deliver a superior user experience.

The Complete Guide to Embedded Analytics is designed for software executives and product managers to answer any and all questions you have on this topic. It will show you what embedded analytics is and how it can help you build product value. It will also explain:

• Whyembeddedanalyticsissohotrightnow

• Howembeddedanalyticsdiffersfrombusinessintelligence

• Howtobuildabusinesscaseandconvinceinternalstakeholderstoact

• Howtoselecttherightsolution

• Thefutureofembeddedanalytics

We’ve also included worksheets that you can use to determine whether your company is ready to invest in embedded analytics and how it will help you improve user experience, attract new customers, and increase sales.

We hope this guide will be your ticket to a new world of more effective, efficient, and lucrative application development.

2Introduction






PART ONE

WHATISEMBEDDEDANALYTICS?

3

Let’sbeginwithadefinition.Embedded analytics is the technology that integrates analytic capabilities into software applications. When implemented successfully, embedded analytics can bring to life the data collected by your applications and provide a superior user experience.

CommonAnalyticsCapabilitieswithinSoftwareApplications

• Dashboardsanddatavisualizations:chartsandgraphsthat display performance metrics

• Staticandinteractivereports:tabularviewsofdatawithor without parameters and scheduling capabilities

• Self-serviceanalyticsandadhocquerying:enablesusersto ask their own questions of the data by exploring a set of data

• Benchmarking:comparingperformancemetricsagainstbest practices from external data

• Mobilereporting:ensuresinteractivefunctionalityonmobile devices and takes advantage of capabilities specific to mobile devices

• Visualworkflows:incorporatingtransactionalcapabilities directly within the analytic user interface, sometimes referred toaswrite-back

EmbeddedAnalyticsDefined

4Part One: What is Embedded Analytics?






It’sallaboutcontext.

Businessintelligence is a set of independent systems (technologies, processes, people, etc.) that aggregate data from multiple sources, prepare the data for analysis, and then provide reporting and analysis on that data from a central view point. It is mostoptimizedforsupportingmanagement-levelleveldecisionsthat require highly aggregated views of information from across adepartment,function,orentireorganization.Thesesystemsarespecifically designed for people whose sole responsibility is to perform data analysis.

Embeddedanalytics is a set of capabilities that are tightly integrated into existing systems (like your CRM, ERP, marketing automation, and/or financial systems) that bring additional awareness, context, oranalyticcapabilitytosupportdecision-makingrelatedtoveryspecific tasks. These tasks may require data from multiple systems oraggregatedviews,buttheoutputisnotacentralizedoverviewofinformation. It is targeted information to support a decision or action in the context in which that decision or action takes place.

HowisEmbeddedAnalyticsDifferentfromBusinessIntelligence?

Said another way, business intelligence is a map that you utilizetoplanyourroutebeforealongroadtrip.Embeddedanalytics is the GPS navigation inside your car that guides your path in real time.

While traditional BI has its place, the fact that BI applications and business process applications have entirely separate interfaces forces users to switch between multiple applications to derive insights and take action. Instead, embedded analytics puts intelligence inside the applications people use every day to improve the analytics experience and make users more productive by combining insight and action in the same application.








By IndustryCompanies across all industries and functions (e.g. marketing, sales, finance) choose embedded analytics to help users make sense of their data so they can make better, more informed decisions. While many business applications rely on embedded analytics to differentiate their products, early adopters (as well as more advanced implementations) have primarily been consumer applications,likeAmazonandKayak.Wewillexploreseveralexamples in detail later in this section.

Commercialvs.InternalAppsEmbedded analytics is about satisfying users’ analytics needs at the exact moment they might question something within the applications they use every day. Software companies have long recognizedthevalueofembeddedanalyticstotheircustomers(and the resulting benefits to themselves), but internal application developers have been slow to integrate capabilities between analytic and operational apps. With the rise of the business user, there is mounting pressure on IT and increased expectations that more people should have access to analytic information. Particularly in large enterprises where most of the operational systems are proprietary, developers are increasingly embedding analytics into these systems to provide relevant information for knowledge workers to make better decisions.

WhoUsesEmbeddedAnalytics?







Usethisworksheet todetermineifyourcompanyisreadyforembeddedanalytics.For each category, select the appropriate number that corresponds with your level agreement (5=strongly agree, 1=strongly disagree). When you’re finished, tally your score to determine your results.

If you scored > 35, you’re ready for embedded analytics.

Ifyouscoredbetween20-35,you’removingin that direction. You should consider getting started with embedded analytics soon.

If you scored under 20, you may not be ready for embedded analytics quite yet. But that doesn’t mean you can’t keep reading!

Flip over to Part 2, and let’s get started!

AreYouReadyforEmbeddedAnalytics?

Factor

Our customers consider analytics to be an important part of our application.

Weneedtofindwaystomonetizethedatacapturedin our application.

We’d like to offer more sophisticated reporting and analytics capabilities within our application.

Our customers are dissatisfied with the level of reporting and analytics we offer today.

We invest too much in development resources to support ad hoc reporting requests.

We are losing deals to our competitors based on their reporting and analytics capabilities.

We could improve our sales demos if we improved the functionality and/or look & feel of our reporting.

Data drives the majority of our customers’ decisions, and we want to capture that value in our application.

Our product generates (or has plans to generate) a significant levelofpersonalizedreportingforeachcustomer.

We plan to migrate to a SaaS environment and question whether our current reporting will be compatible.

StronglyAgree StronglyDisagree5 4 3 2 1







PART TWO

WHYISEMBEDDEDANALYTICSSOHOTRIGHTNOW?

8

Whilereportinginsidesoftwareapplicationsisn’tanythingnew,itwasn’tuntil2009thatGooglerecordedanysignificanttrafficfortheterm“embeddedanalytics,”whichhasincreasedsteadilysincethen.

InterestOverTime

NaturalEvolutionoftheBIMarketIn many ways, the rise of embedded analytics is a natural evolution of emerging analytic technologies and the business intelligence market. From Crystal Reportsinthe90s,toOLAPmulti-dimensionalanalysisat the turn of the millennium, we’re now entering a new wave where users expect to benefit from data analysis in every application they use on a daily basis. Their needs are more varied and require a shift in the traditional BI thinking.

In Forrester’s 2013 Global Tech Market Outlook report, Forrester explains that software companies looking to deliver analytic capabilities should not rely on general business intelligence tools, since these tools often require users to create their own reports, which doesn’t help them to work smarter. Enter embedded analytics, where software companies take care of “the last mile.”

TrendsDrivingEmbeddedAnalytics

9

Source: Google Trends

20072008

2009

20102011

20

40

60

80

100

0

20122013

Part Two: Why is Embedded Analytics So Hot Right Now?






IncreasedDataVolume,Velocity, and VarietyWith so much hype around big data, this one shouldn’t be a surprise. People now expect information to be available at their fingertips – whenever they want it, wherever they are.Yesterday’sfact-findingmissionsthatstartedwithanencyclopedia or a visit to the library have become quick Google searchesonyourphonetofindananswermid-conversation.

Users now rely on technology to comb through massive amounts ofever-changingdatatoorganizerelevantinformationtosolvetheir problems. People need answers quickly, and they choose tousetechnologiesthatoptimizetheanalysisexperienceandanswer questions in a visually attractive way.

DataintheHandsofNoviceUsersData analysis is no longer relegated to a few highly trained, technical people. Ten years ago, most analytics and information delivery was taken care of by IT. In the past several years we’ve seen the rise of data discovery, which takes control from IT and puts it in the hands of power analysts. But even that falls short of today’s needs because ALL workers are now expected to use technology to gain efficiency and increase productivity. Everyone needs to be a “data expert” in their own domain so they can make intelligent decisions that drive business forward.

Thisinfluxofnon-technicalanalystshasforcedBIandotherB2Bsoftware companies to rethink their analytic capabilities and howtopresentinformationinasimple,moreuser-friendlyway.Users expect the software to take care of the last mile instead of pulling information and mashing it together.

ConsumerAppsthatUtilizeAnalyticsCompanieslikeAmazonandKayakhavemasteredtheartofsimultaneouslyprovidingdata-driveninformationanddrivingfrictionless transactions in a seamless manner. These companies haveembracedanalyticstocreateauser-friendlyexperiencethat attracts more users and creates a competitive advantage. As a result, users now expect more from the business applications they use regularly to do to their jobs, which puts pressure on software providers to satisfy their needs.

10

Trends Driving Embedded Analytics (Continued)








Companiesthatprovideembeddedanalyticsintheirapplicationsachievefasterrevenuegrowth.In Forrester’s 2013 Global Tech Market Outlook report, they define a new class of applications called smart process applications. These applications provide:

• Embeddedawarenessdatarelevanttothebusinessactivity

• Embeddedanalyticaltoolsdesignedforthetaskathand

In these applications, analytics is a core capability, such that the lines are blurred between transactional capabilities and analytics capabilities. AccordingtoForrester’sresearch,

Smartprocessapplicationsaregrowingatdouble-digitrates(18%)thataresignificantlyfasterthantheoverallsoftwaremarket(7%).” Forresterestimatesdouble-digitgrowthforsmartprocess applications from $20 billion in 2012 to $28 billion in 2014.

EmbeddedAnalyticsDrivesSmartProcessApplications

ProcessApplications

AnalyticsApplications

SmartProcess

Applications

11Part Two: Why is Embedded Analytics So Hot Right Now?






AmazonAmazonistheGoldStandardforprovidingrelevantanalyticstoencourageon-siteconversion.Fundamentally,Amazonexists to sell books. They have great processes to support the ecommerce experience – including fast shipping, low prices, andBuyNowwith1-Click.ButAmazonalsosatisfiescustomers’informational needs by providing product ratings, video reviews, and suggested products. They’ve added tremendous value by providing relevant analytic information at the point of transaction to create a superior customer experience.

27.1%growth rate in 2012 (vs. 15.8% across Top 500 US ecommerce sites)

B2CApplicationsPavetheWayforEmbeddedAnalytics

Fundamentallyatransactionalapplication(sellingbooks)

Satisfiescustomers’informationalneeds

Tocreateacustomer-friendlyexperienceat the point of transaction.

12

KayakAnothergoodexampleisKayak.Inthiscase,whatstartedoutas a pure analytic application (enabling users to search for flightsandcomparepricesacrossmultipleairlinesandtravelsites) launched an entirely new business model by integrating transactional capabilities at the point of analysis. So not only do you have all of the information you need to choose an itinerary,butyoucanalsoinitiatethepurchasewithintheKayakapplication, without having to reenter your search criteria when youareredirectedtotheairlinebookingsite.NowKayakisableto make money by providing leads to airlines and travel sites like ExpediaandOrbitz.

2012: Closed IPO Day with Shares Up 30%, 2013:

Acquired by Priceline for $1.8Billion

Makesiteasytoinitiate therighttransaction

Fundamentallyananalyticsapplication(flightprices)

To build an entirely new business model around this concept.

Price Trend







Inbusinessapplications,theanalyticsistypicallypresentedinaseparatetab-liketheReportsandDashboardstabsinSalesforce.com.

AfterseeinghowAmazonandKayakutilizeembeddedanalyticsintheir applications, however, this model somewhat pales in comparison. AsAmazoncustomersbrowsetheirsite,theyactuallyfeelsmarterandmore confident that they’re making the right choices. That’s because analytics is a core capability, not an adjunct capability with no real connectiontocommonworkflowsandoveralluserexperience.

B2BApplicationsLagBehindin EmbeddedAnalytics

13

WhatIfI’mBehind?You might be thinking, “But wait! I don’t even have a reports tab. Can’t I take some baby steps first?” The answer is yes. In fact, we recommend evolving your analytics capabilities in phases over time. In the next section, we’ll explore the embedded analytics maturity model, which illustrates the four ways you may choose to embed analytics within another application.







PART THREE

WAYSTOAPPROACHEMBEDDED ANALYTICS

14

In this section, we’ll present the Embedded Analytics Maturity Model, which outlines the various approaches from simple to complex. To set the stage, let’s use the example of GPS in cars to illustrate the innovation model for embedded technologies. As you can see, what started out as a separate product evolved into a corecarcomponent,whichcreatedanewproductcategoryofself-drivingcars.Thesameevolutionexistsforembedded analytics.

What is a Maturity Model?

KEY FEATURES

• Boltedonyour windshield-disjointed user experience

• Novalueforthe auto manufacturer

KEY FEATURES

• Withindrivingconsole- improved user experience

• Automanufacturers capture value

KEY FEATURES

• Highlightgasstations when fuel is low

• Routebasedontraffic and weather

KEY FEATURES

• Createnewwaysof travel(e.g.self-drivingcar)

• Reachnewusergroups (blind, elderly)

• Buildnewbusinesses

Independent GPSDevice

EmbeddedGPSNavigation

IntegratedFunctionality

GPS as a Core CarComponent

15Part Three: Ways to Approach Embedded Analytics







Below are the four stages of the embedded analytics maturity model, which illustrates the progression of increasing integration and product differentiation. Along the bottom are the common elements shared by the coreapplicationandtheanalyticscapabilities,includingdatasource,security,UI,andworkflows.

EmbeddedAnalyticsMaturityModel

Standalone Analytics Application

GatewaytoAnalytics

InlineAnalytics

InfusedAnalytics

Non-Embedded

YourApp

AnalyticsApp

Embedded8% 16% 47% 29%

DistributionofCurrentImplementations(2013 State of Embedded Analytics Report)

16

AnalyticsApp

YourApp YourApp

Module

UI UI

UIData Source Security User Interface Workflows

Part Three: Ways to Approach Embedded Analytics






TheStandaloneAnalyticsApplicationisStage0,becausetheanalyticsarenotembeddedintothecoreapplication atall.Much like the standard GPS device, the data lives in the core application, and the analytics live in another application. The only integration concern is how to get the data into the analytics application.

Data access is typically provisioned through an API or a data export. From a user standpoint, it is a disjointed experience because users have to work with two separate applications, which likely look and operate differently and have no security integration. A familiar example is Microsoft Excel. Users often export data from one application and export it into Excel for analysis, but all they’ve done is create a new version of the data. Once the data changes, the Excel data becomes outdated.

When to Pursue This Model

The most common use for a Standalone Analytics Application is when your product has no business user interface, like Google Analytics. Programmers tag their website or application with a piece of a code to track visitor activity. This visitor activity gets fed into the Google data store, but business users only access that data by logging into the Google Analytics website. Essentially it’s two separate applications, because the data store isn’t intended for business users to see.

Stage 0

StandaloneAnalyticsApplication

17

YourApp

AnalyticsApp







GatewaytoAnalyticsisStage1,wherethecoreapplicationservesasagatewaytotheanalyticsapplication.In this model, the analytics application is integrated with the core application at a security level. Users only need one set of login credentials, which are passed from the core applicationtotheanalyticsapplicationviasinglesign-on(SSO).Notethattherearestilltwo applications, but the access to analytics is embedded in the core application. It’s still a disjointed experience, however, because if users actually want to put insights to use they have to switch back to the core application.


There are three scenarios in which you might choose the Gateway model:

1. You’re working with hybrid architectures

2. Analytics is a distinct offering that customers purchase separately

3. This an intermediate step before moving on to the next stage of embedding

From a development standpoint, you also have separate work streams. Obviously analytics needs access to the data, which requires security integration, but otherwise the functionality is entirely separate from the core application.

Stage 1

GatewaytoAnalytics

18

AnalyticsApp

YourApp







InlineAnalyticsisStage2,andthemostpopularchoiceforembeddedanalytics. Just like the GPS example where functionality is integrated to adjust driving directions based on traffic, analytics now appears within the core application.

Beyond data access and security, analytics is now integrated at the presentation tier and shares the same look & feel as the core application UI. Note that this is the first model where we have just one application instead of two. Inline Analytics is often implemented as a Reports tab or module (as in the Salesforce.com example), but analytics are sometimes presented in other key places as well, like the home screen.


Software providers choose this model when users demand easy and frequent access to analytics. From a work stream standpoint, there is more coordination involved, particularly when it comes to UI, but they can still be separate when it comes to functionality. Most third-partyplatformsandanalyticsapplicationscanbeembeddedusingthisapproach,so there are a lot of options available. Users are also very comfortable with the reports module approach, so it’s not surprising that Inline Analytics is the most common model for embedded analytics.

Stage 2

Inline Analytics

AnalyticsModule

19

YourApp

Module

UI







InfusedAnalyticsisStage3,theholygrailofembeddedanalytics. Just like the GPS example where functionality is so integrated into the car that it creates new forms of driving, analytics is now embedded at the application tier within user workflowsandbecomespartoftheoveralluserexperience.

A good way to think about this model is that if you ripped out the analytics, you wouldn’t haveanythingleft.Youcanhaveacarwithouthighlightingnearbygasstationsoroptimizingdrivingdirectionsfortraffic,butyoucan’thaveaself-drivingcarwithoutaGPS.WithInfusedAnalytics, users are able to view/create analytics to derive insights, and immediately take action.Asuserscontemplateachoice,theycanviewrelevantinformationtooptimizetheir decision. Note that this approach is the only one that qualifies as a smart process application that we discussed in Part Two.


Companies choose this model when their users have sophisticated analytics needs and/or the competition’s analytics implementation is mature.

Keepinmindthatbecausethereisintegrationattheapplicationtier,theworkstreamsneedto be more tightly integrated. Developers working on the analytics will need to coordinate with the developers responsible for the transactional capabilities. Particularly if the backend is hitting backend APIs for data updates or interacts directly with the database, the work streams must be entirely integrated.

Stage 3

Infused Analytics

20

UI







PART FOUR

COMMON FEATURES IN EMBEDDED ANALYTICS

21

Commonembeddedanalyticsfeatures lookalotlikecommon“businessintelligence”capabilities,butwithatwist:theenduserexperienceisintegratedintotheoverallapplication.The capabilities embedded in each application vary, so we have also indicated how often we see each feature implemented:

FeaturesOverview

Common Sometimes Infrequent

22Part Four: Common Features in Embedded Analytics






InformationDeliveryImproving how data is presented to business users is often the top reason software providers look to take on an embedded analytics project. Not only should these capabilities meet the needs of end users, but the look and feel should adhere to the style requirements of the software provider.

23

MobileData is made available to users on mobile devices, ensuring not only the accurate visual display of information, but also be compatible with mobile device features such as touch input.

VisualizationsandDashboardsArangeofvisualizationsareutilizedforusersto quickly draw conclusions and monitor key performance indicators, such as bar charts, line graphs, heat maps, and maps. They can be presented in the context of a single chart, or in a collectionofvisualizationsinadashboard.

ReportsA tabular display of data, often with numerical figures and/or listing of records within categories. Reports can be scheduled for delivery, used in conjunction with thresholds/alerts, or exported to other formats for printing or offline access.

Part Four: Common Features in Embedded Analytics







AnalysisSoftware providers look to enhance the value of their offering by allowing users to perform their own analysis, creating benchmarks and applying proprietary analytics on their own data, and finding innovative ways to incorporate external data sets.

24

External DataIncorporating data from external sources and delivering them into a single view or dashboard, such that the application becomes a vital hub of information.Thiscouldbeintheformofthird-partyindustry benchmarks, data feeds (such as weather and social media), and customer data from their specific data stores.

Self-ServiceAnalysisUsers are given a set of data for which they can filter, create custom calculations, and create their ownreportsorvisualizations.Thedatasetforthe end user is restricted to the particular form of analysis and their user role.

BenchmarkingandDataModelingThis is centered on extracting valuable insights from the existing data in hand and making these insights available in the application. For example, SaaS providers can create performance benchmarks byanalyzingdataacrosstheircustomerbaseandmake this data available for individual customers to compare themselves to. Another example would be applying predictive models to set expectations of future performance.








InteractivityEmbedding analytic capabilities inside of applications presents interesting ways for users to interact with those capabilities, as well as paves the way for a more informed and productive experience inside the application.

25

PersonalizationUserschoosethevisualizationsorreportswhichare most important to them, and place them at the top of a dashboard or create bookmarks that can be accessed quickly.

LinkingThisenablestheusertoclickonavisualizationorreport in order to navigate to a different analytic screen or even another part of the main application, and vice versa. In other instances, the interaction simply changes part of the screen instead of the entire screen.

WorkflowandProcessesBeyond linking, analytics can be more tightly integrated with application functionality. Some examples:chartsembeddedin-contextonanexisting application page to guide user behavior; a report with editable data cells, which enable user toupdatethedisplayeddata;visualizationwithselectable regions (regions of a map or area of a scatterplot) which enable the user to perform an action on the selected records.future performance.








PART FIVE

THEBUSINESSCASEFOR EMBEDDED ANALYTICS

26

Tohelpyoubuildthecaseforembeddedanalyticsatyourcompany,let’sfirstreviewthemajorbenefits.

FasterRevenueGrowthOn average, we find that software companies that embed analytics using the Infused approach have 16% higher annual revenue growth. Revenue growth comes from three distinct areas:

1. Newsales – gain new customers and increase average selling price

2. Customerretention – increase retention rate and average renewal price

3. Salesandmarketingefficiency – increase opportunity and win rates, lower cost per lead

TheReturnonEmbeddedAnalytics:Core Business Case

Create a competitive differentiator

Increase customer satisfaction

Give better sales demos

Improve user experience

Attract new users

Increase overall revenue

Improve your win rate

65%63%

56%54%

41%36%

33%

27

0% 10% 20% 30% 40% 50% 60% 70%

Strong agreement

Part Five: The Business Case for Embedded Analytics






CreateaCompetitiveDifferentiatorOne of the major benefits of embedded analytics is to help you differentiate your product. Many software providers only deliver basic reporting capabilities through their applications, particularly in the business application market. There is still a huge opportunity to create a competitive differentiator by offering more advanced and/or easier-to-useanalyticsinyourapplication,whichprovidesrealvalueto end users. In a recent survey, we found that the most cited benefit of implementing embedded analytics was creating a competitive differentiator,and93%ofrespondentsagreedtheyhadrealized this result.

ImproveUserExperienceWhen implemented properly, embedded analytics can have a profound impact on your user experience. By enabling users to solve problems quickly within your application, as opposed to fumbling around in standalone reports trying to piece together what’s happening, or forcing them to export data to slice and dice in Excel, you make their lives easier. At the end of the day, it’s about minimizingthetimeandeffortthatexistsbetweeninsightandaction.The easier you make it for your users to do something about insights they find in your application, the more value you can capture.

ReduceAdHocSupportRequestsHow many times have you been asked to create a custom report for a customer? And once you deliver that report, the customer comes back asking if you can change this or that, and before you know it you’ve spent a significant number of man hours supporting this request. Multiply that over hundreds of customers and you’re no longer a software company – you’re a development shop. Embedded analytics helps you to bridge the gap between what exists in your application today, and what your customers are asking for, so you can focus on more important things.

28

BenefitsofEmbeddedAnalytics









Deeperintegrationofanalyticsintoyoursoftwareapplicationenablesgreaterabilitytocreateacompetitivedifferentiation.Overall, 65% of software providers strongly agree that embedded analytics is a source of competitive advantage, and that increased to 91% of software providers who choose the Infused Analytics Model.

This is great news if you’re thinking about adding new analytics capabilities, but also if you’re looking to increase the value of your existing analytics by integrating them deeper into your application.

CompetitiveDifferentiatorbyMaturityLevel

CompetitiveDifferentiationfromEmbeddedAnalytics

StandaloneAnalytics

Application

Gateway toAnalytics

InlineAnalytics

InfusedAnalytics

29%46%

65%

91%

29

Source: 2013 State of Embedded Analytics report







Not surprisingly, as you embed analytics more deeply within your application, the more valuable analytics become as a percentage of the overall application.

Note that there is virtually no difference in the value of analytics between the Standalone and Gateway models, but the value more than doubles as soon as you bring analytics into the core user interface.

ValueofAnalytics(RelativetoOverallApplication)byMaturityModel

StandaloneAnalytics

Application

Gateway toAnalytics

InlineAnalytics

InfusedAnalytics

15%

34%

51%

15%

Software providers with Infused Analytics also grow faster than other software companies. The 2013 State of Embedded Analytics study found that companies with Infused Analytics report 16% higher annual revenue growth than average.

30

BuildingProductValueThrough EmbeddedAnalytics








Onceyouestimatethereturnsfromembeddedanalytics,youneedtodevelopthe other side of the business case by understandingtheinvestmentrequired.There are various costs associated with developing/implementing embedded analytics. If you decide to build, your costs will primarily consist of initial development resources and ongoing maintenance and enhancement costs. If you buy a business intelligence platform or integrate with an embedded platform, then your investment will consist of the following: software, development, consulting/training, support, etc.

See page 49 for a further discussion around the build vs. buy question for embedded analytics.

InvestmentandCosts

31Part Five: The Business Case for Embedded Analytics






Choosingananalyticssoftwareprovidertoextendthecapabilitiesinyourapplicationisawaytogettomarketfasterandreduceresourcesoverthelongrun.Theseprovidersmayofferavarietyofdifferentpricingmodels.

CUSTOMER-BASEDPRICINGassigns a cost to each of your customers. This is the most common pricing model since it is easy for companies to predict how many customers they will have in year 1, year 2, and year 3.

USER-BASEDPRICING assigns a cost to each end user of your application. This is a good model for companies with very stable growth, but can be challenging for early stage software companies and high growth software companies since it’s hard to predict how many end users you’ll have in three years, particularly as you start expanding your user base at each customer.

SERVER-BASEDPRICINGassigns a cost to each server. This can be challenging because you don’t want to be limited in your analytics capabilities, or face a steep price increase if one of your customers grows.

Ideally,youwanttofindavendorwhoisflexibleenoughto match their pricing to your business model, so that your analytics capabilities (and costs) are in line with your customer base and revenue forecasts.

OtherInvestmentFactorsMostembeddedanalyticsvendorsofferadd-onsontopof the software licensing costs—including new customer enablement, premium support packages, consulting services, andinstructor-lededucationandtraining.Thepurposeisto accelerate ROI and time to value, and costs tend not to exceed 20% of the software licensing costs. You should also take headcount and hardware costs into consideration, both current state and anticipated costs in the future. The best results come from looking beyond only the software. When you OEM software and make it part of your application, you shouldconsiderwhooffersthebestpackageasalong-termbusiness partner.

32

TheCostofEmbeddedAnalytics








BringItAllTogether

Contact [email protected] tobuildapersonalizedbusinesscasefor your company using our Embedded Analytics ROI Calculator.


Nowit’stimetocombinetheimprovementinanalyticsandtheanticipatedcoststocalculateyourreturnoninvestment.

Thekeystepsare:

Gather baseline metrics such as number of current customers, average selling price, customer retention, and average renewal price

Estimate how embedded analytics will improve your baseline metrics

Estimate the implementation costs, including software, support, consulting, and development costs

Calculate how improved baseline metrics will translate into revenue growth and lower development costs

CalculatingROI


mailto:salesteam%40logianalytics.com?subject=





Insomecases,noteveryonewillimmediatelyseethevalueofaninvestmentinembeddedanalytics.To convince them, you’ll need to understand their priorities, and what challenges stand in their way. Then you can connect the dots for them and position embedded analytics to address their specific concerns.

When you’re trying to gain internal support for an embedded analytics purchase, position it as a potential solution to the current problems your business faces, and how it will impact your customers andthebottomline.Thatwayyourorganizationwillseeitasapriority instead of putting it on the back burner indefinitely.

Your ability to deliver a compelling business case for embedded analytics hinges on how well you structure your argument to resolve the chief challenges and priorities of your audience. No matter which executive you want to convince, make sure to manage expectations about the time to value and effort required. Don’t overpromise and under-deliver.Embeddedanalyticsisnotsomethingyoujustturnonand see instant results. Getting value takes a strong plan, time, and effort. Start small, and evolve your analytics capabilities over time as you and your end users become more sophisticated.

SellingEmbeddedAnalyticsInternally







5TipstoSellEmbeddedAnalyticsInternally

Enhancingourproductthroughnewanalyticshasassistedusinupsellingintothemarketplacetowindealswithlargerenterprises.Duringtheeconomicdownturn,we’vebeengrowingat25percentandreplacingcompetitorswithlargermarketshareatFortune500companies.”

–MikeMercadante,CTO,VPI

35

Understand their goals so you can present a case that meets their needs.

Create a financial case that proves how embedded analytics is the key to accomplishing those goals. If revenue is the main objective, make your case based on revenue.

Discuss, don’t present. Start by asking questions to understand what they are looking to achieve. Then transition by saying, “If I could show you how to meet those objectives efficiently and effectively, would you be interested in learning more?”

Supportyourcasewithreal-lifecasestudies,particularlyfrom companies that are similar to yours.

Bereadyiftheysayyes.Haveyourhigh-levelplan ready, an overview of the next steps, timeframes, and required resources.








HowtoPositionEmbeddedAnalytics forEachExecutive

CEOChiefConcerns:

• Growrevenueand“hitthenumber”

• Managecosts,meetshareholderexpectationsforprofitability

• Attractandretaintalent

• Innovateandout-executethecompetition

• Buildandaligntheorganizationtoenhancecollaboration

• Managerisk

ConnecttheDots:

Contextualizeembeddedanalyticsaskeytobusinessgrowth.Positionitasasolution to create a competitive differentiator so you can become a leader in your space.

Discuss how embedded analytics can enhance sales effectiveness through better demos, shorter sales cycles, etc.

Show how embedded analytics improves the user experience of your product to increase customer satisfaction, and drive new revenue.

Discuss how an embedded analytics platform enables you to go to market faster with new analytics capabilities without sucking up development resources.

CTOChiefConcerns:

• Ensurethattheproduct(s)functionappropriatelyfrom an engineering standpoint over the long term

• Improveproductscontinuallytostaycompetitive

• Buildabetteruserexperience

• Manageandleveragethird-partytechnologiesto deliverrequiredcapabilities

ConnecttheDots:

Educate them on the available technologies and architectures to show howembeddedanalyticsplatformsenablelong-termgrowth.

Discuss how embedded analytics can ease the burden on development to deliver analytics enhancements on time.

Discuss options of working with an embedded analytics partner who is familiar with security, white labeling, and UI/UX requirements so the implementation goes more smoothly and allow their team to maintain their focus on core functionality.







CFOChiefConcerns:

• Manageexpensesandcashflow

• Containrisk

• Enableprofitablegrowth

• Planforthefuture

ConnecttheDots:

Do the math. Present your developed business case. Don’t worry too much about the fact that you’re making estimates, provided that they’re clearly labeled. You’ll build credibility simply by walking in the door with a spreadsheet of numbers, showing you can speak the CFO’s language.

Discuss the notion that embedded analytics helps you save time and resources fielding ad hoc reporting requests from current customers.

37

HeadofSalesChiefConcerns:

• Makequota

• Getanaccurateforecast

• Beatthecompetition

• Expandmarketshare

• Makecustomerssuccessful

• Developthesalesforce

ConnecttheDots:

Remember that sales is on the front lines and often drives product direction based on what they hear from their prospects. Explain how embedded analytics can deliver the analytics capabilities your customers are asking for quickly so their team can start selling it.

Discuss how embedded analytics helps their team to deliver better sales demos, decrease sales cycles, box out the competition, and drive new revenue.

Discuss the value of embedded analytics to end users, which drives increased renewal rates, exposes new opportunities to sell more product, and possibly drives new revenue streams (depending on your packaging model).

ProductManagerChiefConcerns:

• Successoftheproductlinein themarket

• Deliverfeaturesandfunctionality customersareaskingfor

• Deliverasuperioruserexperience

• Maximizecustomersatisfaction

• Meetlaunchdeadlines

• Beatthecompetition

ConnecttheDots:

Build the vision of how the product will be enhanced through embedded analytics – what will their users be able to accomplish and what is the value of solving those problems?

Discuss how embedded analytics is a “need to have” and how it can create a competitive differentiator as well as enhances sales effectiveness through better sales demos, short sales cycles, and increased revenue.

Educate them about the options in the market to add analytics quickly while meeting launch deadlines and maintaining control over UI/UX.

How to Position Embedded Analytics for Each Executive (Continued)







Here are some common reasons why people may delay investing in embedded analytics platform, and how you can overcome them.

TheCostofDelaying

OBJECTION

Idon’tneedtouseathird-partytool because I can build this all internally.

Let’s just give our customers access to the data and let them do what they want.

We don’t have the resources necessary to do this successfully.

RESPONSE

That’s true. With enough time and energy, you can build everything an embedded analytics platform can offer, but do you really want to spend years building analytics?Athird-partyapplicationallowsyoutodevelopfasterandsavemoneyso you can maintain your focus on advancing your core functionality. Embedded analytics has evolved to the point where hundreds of companies spend 100% of their time trying to make analytics better, faster, and easier for end users. By utilizingathird-partyplatform,youcandowhatyoudobest,whilerelyingonanalytics experts to make your product better.

You’re leaving value on the table, and instead of enabling end users to do their jobs more intelligently, you’ve settled for becoming a data collection tool. Besides, data exports are no longer going to cut it – your customers expect more. By only providing exports, you’re inviting your customers to come back frustrated with custom reporting requests that eat into your time.

Allthemorereasontointegratewithathird-partyplatform,whichbringsthedomain expertise necessary to implement embedded analytics successfully, includinghow-toguides,bestpractices,andin-personconsultations.Youcanstartsmall, or look for tools that conform to your architecture and your development process.ThedaysofBigBIareover-therearesomegreatoptionsthatwillenable you to add real value to your applications without taking over everything.








OBJECTION

We know our customers want something but we don’t know exactly what it is they want.

Embedded analytics is a nice to have, not a need to have for us.

RESPONSE

If your customers are communicating some sort of pain, you need to investigate what’s driving that frustration. A good embedded platform will support you through a structured evaluation process where you build a proof of concept together, which you can use to validate your direction with your customers. In this case, it’s important to choose a platform that is easy to use and supports rapid prototyping so you can pivot appropriately. You can also rely on embedded analytics platforms to guide you in how to package an analytics offering for your customers based on their requirements.

Educate them on the evolution of embedded analytics within B2C and B2B applications, and how it is most definitely a need to have. Show how embedded analytics builds product value and enables your users to work more productively with your application. Present findings from the 2013 State of Embedded Analytics study, which outlines the clear benefits of embedded analytics, including creating a competitive differentiator, improving sales demos and conversion rate, and faster revenue growth, to support your case.

Bottomline:there’sneveraperfecttimetorolloutnewsoftwareorstartanewproject.Don’tletthedelaygoontoolong.You’llalwaysbebusy.Onceyou’vedeterminedyou’llbenefitfromtheinvestment,thelongeryouwaittoimplementembeddedanalytics,thelongeryou’llwaittoseeapositiveimpact.








PART SIX

HOWTOBE SUCCESSFULWITH EMBEDDED ANALYTICS

40

TheEmbeddedAnalyticsGo-to-MarketPlanBeing successful with embedded analytics requires more than great technology. While there are important differences between embedded analytics platforms, success is primarily determined by your strategy and ability to execute. Here is your go-to-marketplantoimplementembeddedanalyticssuccessfully.

UserExperience

BusinessValue

User Profiles

Capabilities Map

Implementation

Packaging & Pricing

Agile Development

Build vs. Buy

MarketDelivery

Promotion

Sales Enablement

Education

41Part Six: How to Be Successful with Embedded Analytics







Repeatthismantra:Icreatevalueinmysoftwarebysolvingcustomerproblems.The power of data is your customers can leverage your application to:

• Deriveinsightsfaster

• Drawaccurateconclusions

• Increaseefficienciesandproductivity

• Reducecosts

Step1-DefinetheUserExperience:

CreatingUserProfiles







Whenplanningtoimplementembeddedanalyticswithinyourapplication,you’llneedtodetermine:

• Whatproblemsdoyourusersneedtosolve?

• Whatinformationdotheyneedaccessto?

• Whatdatasourcesdotheyneedtoconnectto?

• Howoftendotheyneedaccesstoanalytics?

• Willstaticoutputbesufficient,orwilltheyneedtobeableto explore data, create their own reports, etc?

• Aretheyinterestedinbenchmarkingperformance against their peers?

• Whereandhowwilltheyaccesstheanalytics(e.g. mobile devices while on the road)?

• Canyouincreaseadoptionorattractnewusertypes by adding specific analytics capabilities?

Thesequestionscanhelpyoufleshout the user roles for your product, which will inform your technical and functional requirements. Use the template below to define your user roles and their pain points, their transactional/analytical needs, and how your product addresses them.

Role

Behaviors

Attitudes

Motivations

Barriers

HowWeHelp

USER 1 USER 2 USER 3 USER 4

43

Creating User Profiles (Continued)

Part Six: How to Be Successful with Embedded Analytics






Onceyou’veidentifiedyourdistinctusertypes,useacapabilitiesmaptomatchthemwithrelevantanalyticscapabilitiesrequiredinyourapplication.You may find that there is a lot of overlap in terms of the analytics capabilities required by your user types. That makes your job easy – simply focus on delivering those capabilities first. However, you may find that there’s no overlap at all, and that you have distinct user types that all want different things. Usually you’ll land somewhere in the middle, where you have some users who need mostly static dashboards and reports (like executives), and other users who need the ability to slice and dice data, create their own reports, etc. (like power users).

Step1–DefinetheUserExperience:

UsingaCapabilitiesMap

Write backs

CustomizableReports

Drilling/linking

Scheduling/Exports

Interactive Reports

Static Reports

Reports

VisualWorkflow

CustomizableDashboards

Interactive Dashboards

Static Dashboards

Individual Charts / Graphs

Visualizations

Creating Reports

Creating Visualizations

Multi-Dimensional

Data Analysis and Exploration

Data Exports

Self-Service

Benchmarking

User Data

Third-Party Data

Cross-Module Data Joins

Mobile

OtherCapabilitiesUSER TYPE 1

USER TYPE 2

USER TYPE 3

44

SampleCapabilitiesMap







Nowthatyou’veidentifiedyourusersandtheiranalyticsneeds,youneedtodeterminehowtopackageandpriceyouroffering.There are three common packaging models employed for embedded analytics:

• Tieredmodel – multiple editions, each with increasing analytics capabilities (see example below)

• Single,separatemodule – all analytics capabilities in one offering, separate from the core application

• All-inclusivemodel – standard core offering includes infused analytics capabilities

Step 2 – Implementation: PackagingOptionsforEmbeddedAnalytics

45

Write backs

CustomizableReports

Drilling/linking

Scheduling/Exports

Interactive Reports

Static Reports

Reports

VisualWorkflow

CustomizableDashboards

Interactive Dashboards

Static Dashboards

Individual Charts / Graphs

Visualizations

Creating Reports

Creating Visualizations

Multi-Dimensional

Data Analysis and Exploration

Data Exports

Self-Service

Benchmarking

User Data

Third-Party Data

Cross-Module Data Joins

Mobile

Other Capabilities

Silver

Gold

Platinum

SampleCapabilitiesMapwithTieredPackages







Tiered Model • Baseofferingwithlimitedfunctionality,sometimeslends itself to a freemium model

• Morecapabilitiesareavailableathighertiers,analytics can be distinct options by themselves or bundled with other application functions in each tier

• Priceforeachtiercanberelativetothebasepriceand structure (usage model) or a fixed dollar amount

The tiered model is appropriate when you have distinct user types with different analytics needs, or specific analytics capabilities that are inherently more valuable than others. In general, you can define the tiers by 1) business value – base set of report/data access vs. expanded set, 2) user type – report reader vs. report writer, or business/functional role, or 3) capabilities – reports vs. dashboards vs. self service analytics.

Single,SeparateModule• Notiers,justoneoptionalanalyticsmodule

• Typicallychargedasaseparatelineitem

• Singleadditionoptionforagivenprice

The single, separate module is less common today than six or seven years ago. Now, it’s really only appropriate when you have a very homogeneous group of users with only basic reporting needs.

46

Packaging Options for Embedded Analytics (Continued)

All-InclusiveModel• Analyticscapabilitiesarepositionedascoretothe overall application value

• Typicallynotchargedforseparately

• Valueisbuiltin

Theall-inclusivemodelisbecomingincreasinglycommonasembedded analytics trends towards the Infused model where it is a core component of the overall application. In this case, software providers typically CAN justify a price increase for their application because the value is higher. If you are in a particularly competitive and/or sophisticated market, however, the value of embedded analytics often manifests itself in a higher win rate and/or higher retention rate instead of a price increase. Customers don’t want to pay more for it because everyone has it, but they’ll choose your solution over others because the value is still there.








Onceyou’vedecidedhowtopackageandpriceyour analyticsoffering,herearethreetipstocompletinga successfulimplementation.

HaveaVision,butBuildinPhasesWhen you start building specific analytic capabilities into your application, it can sometimes become overwhelming as you see how far you have to go to complete your vision, particularly as new ideas surface along the way. That’s okay. Before you try to bite off the whole ocean, remember to start small and build from your successes. Start with one user type, one problem, one report. Get feedback and move forward. Requirements shift and evolve over time as users start to see what’s possible, so it’s important to stay agile and approach embedded analytics in many iterations and phases.

Where should you start?• Bybusinessproblem

• Byroleofcustomer

• Bycapabilities

Keepinmindthatyoumayhavetodecidebetweenimplementingthe most valuable items vs. the mostwidelyutilizedfeaturesfirst.

Bottomline:Walk before you run.

Step 2 – Implementation: TipsforaSuccessfulEmbeddedAnalyticsProject







InvolveInternalandExternalStakeholdersThere’s nothing more frustrating than building out a really cool feature that no one uses. To avoid this, be sure to get regular feedback from internal and external stakeholders as you build specificanalyticscapabilitiesintoyourapplication.Utilizescreenmockups early in the process and review them with current customers to validate your direction. Ask what they like, what they don’t like, how they would use it, and what suggestions they have to make the product better. This will help you to stay focused on solving real user problems with embedded analytics, and also enables participants to become advocates when the capabilities become generally available.

PerformaUsabilityStudyto IdentifyGapsWith select customers, you should consider conducting on-siteusabilitystudiestoseehowtheyactuallyusetheapplication and identify remaining gaps. The point of conducting a usability study is to find out in advance what problems will bother your users, so be prepared for users to complain when they are lost or frustrated – that’s exactly the kind of feedback you’re looking for. Avoid helping users to get to the right answer. Instead, ask them to complete specific tasks and learn how they expect to navigate your application to accomplish them. Ask them to rate certain aspects of the application,andprioritizeenhancementrequests.Askopen-ended questions to get the most feedback, not questions that can be answered with yes or no.

48

Tips for a Successful Embedded Analtyics Project (Continued)








Thebuildvs.buyargumentisincreasinglyirrelevantforembeddedanalyticsasuserexpectationsbecomemoresophisticated.There are many companies in the analytics space, whose sole mission it is to make analytics better, faster, and easiertouse.Forthisreason,softwarecompaniesareincreasinglymorelikelytointegratewithathird-partyembedded platform, but regardless, here are the three options available to you.

Step 2 – Implementation: Buildvs.Buy

Option1:Build

Often the first option companies choose because their requirements seem simple.

•Code-intensiveapproach

•Developmentwiththird-partycharting libraries, or open source code

Pros

•FlexibilitytocreatethedesiredUX

•Lowcostforlow-complexityprojects

Cons

•Costofdevelopment,support,and maintenance over time

•Timetomarketpoor

•Usuallyacode-intensiveprocess

Option2:IntegrateaBIApplication

The best option if your requirements truly are simple, you are okay with a disjointed UX, and your deadline is very tight.

•Integration-centricapproach

•Bolt-onthird-partyapplication

Pros

•Fastertoacquireout-of-the-boxfunctionality

•Lesscodingoffunctionality

Cons

•NeedforspecializedBIskillsetsfor development and integration

•LessabilitytocraftyourownUI/UX

•Hardertosupportadvancedworkflowsforyour end users

Option3:EmbeddedPlatform

The Goldilocks approach…most of the functionality you need, without being too restrictive.

•FlexibilitytocreateUI/UX

•Quicklyacquireandconfigurefunctionality

•Utilizeexistingresourcesandskillssets with minimal coding required

Pros

•Acceleratedtimetomarket

•FlexibilitytocreatedesiredUI/UX

Cons

•Needstrongpartnerasvalueiswrappedupinathird-partytool







You’veembeddedanalyticswithinyourapplication…nowwhat?Herearesometipsforgettingthemostoutofyourinvestment.

PromotionBestPractices

Be VisualAnalytics are inherently visual, so the best way to showcase yournewcapabilitiesistoutilizecompellingvisuals.Usescreenshots liberally on your website and sales decks, and use webinars and videos to guide users through your new features.ConsidercreatingaVisualGallerywithtopicalorcustomer examples.

LeverageCustomerStoriesTo convince prospects of the value of your application, nothing is more convincing than customer stories. Reach out to your customers regularly to solicit feedback, and ask if you can quote them in a case study, webinar, press release, and/or testimonial on your website. Consider creating a Testimonials section and/or Customer Success Gallery to present all of your happy customers in one place.

Step 3 – DeliveringEmbeddedAnalyticstoYourMarket







SalesEnablementAs you roll out new analytics capabilities, be sure that your sales team knows what’s coming and how to sell it effectively. You’ll need to craft new messaging, determine the new value propositions for each of your user types, and train the sales team before launch. Remember to share new use cases and teach the sales reps to identify when and how to target new user types. Create compelling demonstrations that highlight the most valuable capabilities, and how your product is different from competitors. Prepare interesting demo data to simulate a rich production environment. Once you get rolling, remember that sales is on the front lines and is capturing a ton of feedback from prospects, so be sure to close the loop so that feedback informs future development plans.

ThinkEducationToday’s selling process has transformed into an education process. Yourprospectsneedtorecognizeyourcompanyasathoughtleaderthat understands their frustrations and challenges before they’ll agree to a sales pitch. Educate your potential customers through compelling content aligned with each stage in the buying process, including white papers, solution briefs, topical webinars, buyer’s guides, RFP templates, and demos.

Tipforcapturingtestimonials:While you’re on the phone with customers, ask if they would be willing to provide a testimonial. If they say yes, send them an iPad in the mail and have them record a short video on their experience with your product via FaceTime. Then let them keep the iPad as thanks for theireffort!It’sawin-win.

51

Delivering Embedded Analytics to Your Market (Continued)








PART SEVEN

BUYING AN EMBEDDED ANALYTICS SOLUTION

52

Great!You’vedecidedtobuyanembeddedanalyticsplatform.Nowyouneedtoselecttherightsolution.Of course, in our (admittedly biased) opinion, Logi Analytics is almost always the best solution. But here’s an unbiased process you can follow to buy the embedded analytics solution that is right for you.

DetermineYourGoals&TimelineTo get where you want to go, write it down. Statistically speaking, you increase your likelihood for success simply by putting your goals on paper.

Hardmetricsmaybe:

•Decreasesalescycle

•Improvewinrate

•Improvecustomerretention

Softmetricsmaybe:

•Createacompetitivedifferentiator

•Givebettersalesdemos

•Improveuserexperience

BuyingProcess

53Part Seven: Buying an Embedded Analytics Solution






Identify the steps you’ll take to get where you want to go. You aren’t ever “done” with embedded analytics, so build time to evolve and learn from your customers. Ask yourself, “When do I want to…”

•Starttheselectionprocess?

•Havedetailedvendorpresentationsanddemos?

•Finishaproofofconcept?

•Makemyfinaldecision?

•Startdevelopment?

•Gotomarket?

IdentifyTechnicalRequirementsReview your administrative, integration, and technical requirements. Research your competitors and talk to your customers to develop a firm understanding of the capabilities you want to add to your application. What other technologies do you have that the analytics will need to work with? What data sources will you need to access? What level of integration are you looking for with your core application? Reference the functionality checklist in Part Four to certify you’ll get what you need today and in the future.

TheImportanceofEasyItshouldbeeasytogetstartedquickly, so you can bring your product to market sooner. Get all of your major questions answered during the structured evaluation so you are confident in your choice.

Itshouldbeeasytodevelopanalytics, so you can meet all of your capability requirements while maintaining focus on advancing your core functionality.

It should be easy for anyone on your developmentstafftouse,not just a select few.Gowithaplatformthatutilizesopenstandards and offers an intuitive development experience.

Consider who will use the platform to create analytics and their current skill set. How important is ease of use? What level of additional services, training, and support will you need?

Turn the requirements into functional scenarios. Describe how you want your users to interact with your application once you’ve embedded analytics, and what they’ll be able to accomplish.

54

Buying Process (Continued)

Part Seven: Buying an Embedded Analytics Solution






AssembletheTeamDetermine the stakeholders that need to be involved. Who is going to care about embedded analytics internally (executive team, product management, lead developers) and externally (key customers, customer advisory board)? Be sure to review the technical requirements with them upfront, and build the business case collectively to get buy-intomoveforward.

Research Potential VendorsAssign a point person to research potential vendors and evaluate whether their functionality matches your requirements. Look at industry sources like the Gartner MagicQuadrantforBIPlatformstocreateyourinitiallistandpayattentiontoplatformsthatspecializeinthe OEM market.

Get demos from each one and confirm a basic fit. Discuss your requirements and ask each one to demonstrate how they would deliver your specific processes and scenarios. Ask tough questions and make sure the vendor actually shows you that they have what they say they have in terms of functionality. Confirm ballpark pricing to move forward.

Evaluate each vendor’s ability to make you successful during the implementation process through access to best practices, community, consulting, support, and training.

Avoidafeaturebake-off.Instead,focusontherequirements you identified in step 2, and try not tobedazzledbyfeaturesthatdon’tdeliveronyourcriteria. Of course during your search process you may update your goals as you learn what’s possible, but stick to what you can envision yourself using that will provide value to your customers.

CompleteStructuredEvaluationswithSelectedVendorsNarrowdownyourlisttothetop2-3vendorsandbegin a structured evaluation process with each one. This is where you’ll define a proof of concept and establish clear cut guidelines for what you want to accomplish within, say, 30 days. The amount of interaction you have with each vendor is based on your preference – ranging from an assisted trial where support is generally available if you run into issues, to a true structured evaluation where you and the vendor are building a proof of concept together.

At the end of the evaluation, present the output back to the stakeholders to get feedback and validate your direction.

55








TalktoReferencesNow it’s time to find out if your vendor can actually make customers like you successful.

Ask your vendors for references. Solicit others from your personal and social networks. Look for references that aresimilartoyourorganization(size,industry,use case, etc.).

Find out whether your situation is similar to theirs. Don’t just ask whether they’re happy with the vendor, drill into what functionality they’ve delivered, what is support and training like, how long was implementation, what roadblocks did they run into, how did the vendor handle any problems or issues?

TheImportanceofFlexibility Youknowbesthowyourusersprefertoworkwithyourapplication,so you should absolutely maintain control over the UI/UX. Choose a platform that fits into your overall product vision, not the other way around.

Youdon’twanttoinvestalotoftimeandenergywithaplatform,only to rip it out a year later. While you don’t want unnecessary complexity, you don’t want to outgrow the solution either. Going too small or cheap—without aligning to your future requirements—is a clear path to failure.

Whenyouintegratethird-partytechnologyintoyourapplication,the licensing needs to make sense. Look for vendors who can tailor their licensing to match your business model.

56








QuestionstoAskDuringaReferenceCall

SuccessCriteria&Selection

• Whatwerethekeybusinessprocessesandgoalsyousetforthisembeddedanalyticsproject?Howwellhasthe system delivered on those goals?

• Wereyouthedecisionmakerresponsibleforpurchasingthissolution?

• Whatmadeyouchoosethesolutionyouselected?

Implementation&Ramp-up

• Tellmeaboutyourimplementation–whatwasbetterthanexpectedandwheredidyourunintochallenges?

• Howlongdidittakeyoutolearnbasicfunctions,likecreatingadashboardorreport?

• Howcompleteistheintegrationbetweentheanalyticsandyourcoreapplication(includingsecurity,whitelabeling, etc.)? How hard was it to set up and maintain?

• Whathasyourexperiencewithtrainingandsupportbeenlike?

• Howproactivehasthevendorbeentomakesureyouaresuccessful?

Results

• Haveyoudeployedyouranalyticssolutionyet?Ifso,whatwasthereactionlikefromyourcustomersandprospects?

• Haveyouseenanyspecificbenefits–liketimetomarket,competitivedifferentiator,bettersalesdemos,increasein customers, and/or increase in revenue?

• Whatdoyouloveaboutthisplatform,andwhatdoyouhate?

• Beyondthelicensing,whatothercostsdidyouincurduringimplementation?

• Ifyouweretodothingsoveragain,wouldyoumakethesamevendordecision?Wouldyoudoanythingelsedifferently?








Select a Vendor and Get StartedIt’s go time! Choose the vendor that you feel most confident in as a partner to reach the goals you identified earlier in the process. Of course you’ll have to compare and negotiate terms and conditions, but look beyond software for the vendor who gives you the highest chance of success. Make sure your vendor has the resources to help you, even if you don’t need the help today. Later on, you’ll appreciate being able to test ideas and leverage best practices as your needs evolve. Get training for those who will be using the platform to create analytics. Create your first set of reports. Work with your vendor’s enablement and consulting teams for best practices.

Monitor,Adapt,andOptimizeThere’s a lot that could be said here, given how endless your possibilities are when using embedded analytics. But for the purpose of time and space, here’s an overview of how to approach this phase of your process.

•Investinthetrainingyouneedtobesuccessful.

•Afterthreetosixmonths,doacheck-up,andconsider reengaging with your vendor’s services. Evaluate additional services that could take you to the next level.

•Engagewithyourvendor’scommunitytolearnand share best practices. Suggest ideas for new features while you’re at it.

Customerreactionshavebeenastounding.Customersareparticularlyinterestedinthisportionduringthesalesprocess.Additionally,wefindthattheyengagealotmorewiththereportingbecausetheycancontrolitandinvestigatewhatthey’reseeing.Thenewdashboardsandreportshaveenabledthemtoseemuchquickerresults.”

– Andy Madge, Head of Technical Services, CreativeVirtual

58








Beyondthefeaturesandfunctionalitypreviouslydiscussed,hereisalistofadditionalfactorstoconsiderwhenselectinganembeddedanalyticsvendor.

Implementation&Ramp-up

• Howlongdoesittaketogetliveatabasiclevel?Amediumlevel?Anadvancedlevel?

• Doyouprovidetrainingliveoron-demand?

• WhatskillsetswillIneedonmyteamtobesuccessful?

Service&Support

• What’syourservice-levelagreementfortechnicalsupport?

• Howwillyouhelpexposeouruserstonewideasandbestpractices?

• Howactiveisyouronlinecommunity?HowquicklywillIgetanswers?

• Whoareyourkeyservicepartners?Whoprovidesstrategyandprocessdesign,change management, and technical integration support?

LikelihoodforLong-TermSuccess

• WhatkindofongoingcostsandresourcesshouldIexpect?

• Isyourcompanyviableinthelongrun?Whatfundingandcapitaldoyouhave?What’syour growth rate?

• Howwelldoesyourproductroadmapalignwithmyfutureneeds?

Additional Factors to Consider







PARTEIGHT

THEFUTUREOFEMBEDDED ANALYTICS

60

Embeddedanalyticsisanewanddynamicindustry,andwe’reseeingnewcapabilitiesallthetime.Herearethethreekeytrendsthatwilldrivethisevolutionoverthenextfewyears.

InfusedAnalyticsBecomestheStandardAs we discussed in Part Three, we are seeing a trend towards the Infused Analytics model, where analytics becomes a core component of the parent application within a seamless user experience, such that it’s impossible to tell the difference between thetwo.Embeddedanalyticsenablesworkflowsouserscanderive new insights, draw accurate conclusions, and identify ways to increase productivity and decrease costs. Just as B2C applicationshaveevolvedfrombolt-approachestomoreinfusedimplementations, B2B applications will follow suit so users are able to access analytic information and initiate transactions without leaving the core application.

TheFutureofEmbeddedAnalytics

61Part Eight: The Future of Embedded Analytics






AnalyticsEverywhere,forEverybodyWe’vealreadystartedtoseetheincreasedneedforself-service capabilities.Relatedtothistrend,weanticipatemorenon-technicalusers to start demanding access to analytics within the software applications they use on a daily basis. This has repercussions on the user experience required for those applications, as analytics willneedtobeextremelyeasytouse,withbuilt-incontrolssoeven novice users can arrive at accurate conclusions. The days are gone that a few power users do 100% of the analysis and share the results with the rest of the team. Now all team members will want direct access so they can do their jobs more efficiently. You’ll likely still want to provide basic reports for the majority of your users, but prepare for more users wanting control over the output. Your product management and developers will be more challenged by self-servicethantheyeverwerebymanagedreporting.It’sharderto enable your users to ask their own questions than it is to provide dashboards that answer a few key questions. Eventually you will need to deliver both.

MoreSophisticatedAnalyticsCapabilitiesHopefully it’s obvious by now that embedded analytics is here to stay and that it is a need to have for all software applications. Your customers expect it, and you need to meet their expectations to stay competitive. However, the sophistication of analytics is still pretty basic across the board. If you think about the range of analytics from least to most advanced, you might have:

• Descriptiveanalytics – describe what’s happening with the data (e.g. sales are going up, and here’s a chartthat’s showing that)

• Diagnosticanalytics – no longer just describing, now diagnosing what the issues are (e.g. West Coast sales have plummeted; this is something you need to address)

• Predictiveanalytics – here’s the data, here’s what it means, and here’s what the next quarter is going to look like

• Prescriptiveanalytics – here’s what’s happening, here’s why, here’s what the future looks like, here’s what you should do about it

While 93% of software companies provide some level of analytics within their applications, few are delivering prescriptive analytics, where they not only present what’s happening, why, and what the future looks like, but also offer direct guidance to solve the problem. If you think about it fromanend-userperspective,thatprovidesalotofvalue.And in the end, isn’t that what it’s all about?

62

The Future of Embedded Analytics (Continued)

Part Eight: The Future of Embedded Analytics







PART NINE

LOGI ANALYTICS’ APPROACHTOEMBEDDED ANALYTICS

63

LogiAnalytics’ApproachtoEmbeddedAnalytics

WhyLogiAnalytics?ArchitectureMadeforEmbeddingLogi Analytics offers the best platform to quickly create, integrate, and iterate upon embedded analytics with minimal impact on development resources and infrastructure.

FastestTimetoMarketOurdevelopmentapproachenablesyoutoquicklyassemblepre-builtelementstocreateevencomplexdatavisualizationsandanalyticswithminimal coding.

Your Partner for SuccessLogi Analytics has a fully dedicated OEM team and over 10 years of experience helping hundreds of software companies to embed reporting, dashboards, and analytics. From visual design to feature selection and integration strategies, we’ve developed best practices for every situation and will work with you to make them part of your application.

Seamless.Fast.Complete.InteractiveDashboardsandReportsDeliversuperiordatavisualizations,charts,andgraphics

Self-ServiceAnalyticsEnable power users to create their own reports and explore data

Mobile-ReadyDevelopmentDeliver content on mobile apps through HTML and HTML5

SeamlessUserExperienceYour users will never know Logi is running behind the scenes

ElementalDesignApproachUsepre-builtelementstocreateanalyticswithminimalcoding

SecuritythatMatchesYourApplicationFlexible and highly granular security layer ensures proper access for all users

CloudorOn-PremiseSupportIncludingsingle-instance,multi-tenantSaaSenvironments

ExtensiblePlatformCreate a uniquely tailored user experience for your application

LicensingtoMatchYourBusinessCustomizedlicensingalignedtoyourbusiness

Visitwww.logianalytics.com/oem-solutions to learn more.

64Part Nine: Logi Analytics’ Approach to Embedded Analytics






ConclusionSo there you have it: everything you ever wanted to know and more about embedded analytics. Whether you’re building your first product or revamping an existing one, embedded analytics can help you solve real customer problems, which builds product value and creates a competitive differentiator to propel your business forward.

HAPPYDEVELOPMENT!

ContactLogiAnalytics

NorthAmerica:+1703-752-9700

Europe: +44 118 935 7256

Email: [email protected]

#CG2EA

Website: www.logianalytics.com

Blog: www.logianalytics.com/blog

Twitter: @logianalytics

65


mailto:salesteam%40logianalytics.com?subject=

http://www.logianalytics.com

http://www.logianalytics.com/blog

https://twitter.com/LogiAnalytics





Technology

The Complete Guide to Embedded Analytics