A revolutionary new analytical toolset for the relationship marketing space, Nexus Insight Builder is a fun, and yet powerful business intelligence software tool that leverages your integrated Nexus 360 data in order to provide rapid fire business intelligence and market discovery.

Simply put, Nexus Insight Builder is an intuitive drag-and-drop tool that lets you find immediate marketing insights through the fun and easy exploration of your integrated customer and marketing activity data.  Anyone comfortable with something like spreadsheet software can get up to speed quickly on Nexus Insight Builder and yet have much, much more power.

Here are a few ways that Appature Nexus users can use Nexus Insight Builder:

Too much data for your business?  Not a problem for Nexus Insight Builder.  Both Marketing and Analysts can connect to their integrated, cleansed, and de-duplicated Nexus 360 customer database to extract data into our in-memory data engine and get fast response times on data sizes of 10 million, 100 million, or even 1 billion records.

They can analyze any data of any size using an easy drag-and-drop interface requiring little to no training.  IT directors and commercial operations like using Nexus Insight Builder because it makes Business Intelligence (BI) fast and easy to maintain.  Marketers feel liberated with access to information, while IT can be sure of security and control.

Please contact your account management team soon in order to schedule a walk-through of this exciting new capability!

If these challenges sound familiar, Relationship Marketing might be the answer. Relationship Marketing is a multidiscipline, cross-channel, long-term marketing strategy that advocates knowing your customers – who they are and how they act, in different channels at different points in time – and using this knowledge to make marketing, sales or customer support decisions.

Check out our CEO’s latest thoughts on Media Post to learn more about how Relationship Marketing is changing how healthcare marketers reach customers.

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The idea of leveraging data to better meet customer needs has paid off in a big way in many industries. So what does this movement mean for healthcare and life sciences, which has historically been constrained from creating similar consumer experiences? Read further to learn how Appature is using data to improve patient outcomes

Kabir Shahani, CEO of Appature explains how his company is creating cloud based tools to help customers create unique experiences for HCPs and other end users.

Connecting the dots between sales and marketing in healthcare, Appature Nexus launched on the SalesForce.com AppExchange.

In response to healthcare marketers cries to close the communication gap between sales and marketing, Appature has been successfully integrating with common sales force automation (SFA) tools in healthcare for years now. With SalesForce.com becoming exceedingly predominate within the healthcare marketing space, we are ecstatic to announce that the Appature Nexus connector to Salesforce.com is now available on the SalesForce.com AppExchange.

Enabling a key sense of transparency and facilitating effective communication between sales and marketing has been incredibly important to Appature customers. As I mentioned in a previous blog post last year, we most commonly find the following integration needs in healthcare marketing:

- Keeping sales in the loop about the activities of marketing and their HCP targets

- Keeping marketing in the loop about the person to person sales activities in the field

- Treating the sales force as customers with marketing emails, surveys and calls to action

When these three major capabilities are in place, what we find is that our customers are finally able to achieve “coordinated messaging”.  A state where your HCP targets are not receiving disjointed communications about your product, sales is always kept up to date on key marketing activities and marketing has the insight they need to drive excellent programming.

Through Appature Nexus’ new presence in the Salesforce.com AppExchange, Appature is very excited to treat this common “customer communication ailment” for those currently using the Salesforce.com platform.

Does this sound like you too?  Let us know your thoughts below.

To keep up with the latest news, signup for our Relationship Marketing Digest.

Google, and other search engine developers, helped pioneer a new approach to working with large data sets that rejects the limitations of traditional relational database technologies.  They knew all too well that if you tried to index the entire internet with a traditional database, waiting for hours for an answer would be the expected result.  This problem is not limited to indexing the web, however.  You don’t even need to deal with the entire internet  before you can get into trouble with relational databases.  The real problem comes about when you want to be able to ask arbitrary questions of data, not just pre-canned questions, and get those answers back immediately.

In the Healthcare industry there is more than enough data available to get into trouble.  From web traffic on multiple brand websites and micro-sites, internal and purchased demographic data, HCP prescribing behavior, opt-in preferences, campaign touch points, sales rep interactions, the social web, and opt-in patient information, record counts can easily reach into the billions and beyond.  Data sizes for a single company can total terabytes or more.  Asking questions of this amount of data is easy if your needs are constrained.  It is hard if you want to do this near real-time and ad hoc – which is where we see the real need, and what we aim to enable for all our customers

In the past, healthcare marketers only solution has been to hire service providers that deploy relational databases, a lot of expensive hardware, and no shortage of outsourced service hours.  Or worse yet, service providers have been unable to fully enable this type of querying and segmentation, or have been forced to use sub-par software which then frustrates their customers.  Finding viable answers to the question “who should I be targeting and when?” has taken months and worse, involves 7 to 8 figure price tags.

Clearly, there are many reasons why this state of affairs exists, and not all of them have to do with technology.  Strategic vision (or lack thereof), process challenges, and volatile workforces all contribute to expenses typically found in the cost of finding customers and growing market share.  That being said, enabling technology has a significant role to play in helping marketers and their service providers collaborate to make informed decisions.

One of the reasons that aggregated data is often hidden from brand managers is that the technology used to assess it isn’t designed to answer ad hoc questions on large amounts of data in a fast and user friendly way.  This leads to interfaces that, if a brand manager were to use them, would return results in hours, not seconds.   A long time to information makes it nearly impossible for brand managers to do their own exploration.  Brand managers are forced to throw additional outsourced service resources at a problem just to get started.  True collaboration at the data layer is far more a dream than reality.  In the end, brand managers wind up in the back seat of a car they should be driving and their internal IT departments have no way to help them.

A question that is raised here is why do relational databases and traditional on-premise software solutions fail to deliver?  There are a number of reasons for this, but to illustrate the point, let’s consider an analogy.

Imagine a Super Market.  Now envision the aisles of this Super Market filled with products of all different shapes, colors, pictures, brand names, inventory numbers, shelf positions, and prices.  If your super market was small, and you wanted to find a can of beans with a green label, you could use just about any strategy you please and find that can in a reasonable amount of time.

But, when the supermarket is large, like a Costco, and you need to find bean cans with more specific criteria like “the number of green cans of beans with the word ‘fresh’ somewhere on the label, a picture of a farm house, and a price between $2 and $3 per can”, getting an answer will begin to take a lot more time if you don’t have the right strategy.  Translating this type of problem to relational database land, one might try to store all the products in a database (think shelves) and create indexes (think signs) for commonly asked questions.  Indeed, if you typically want to know how many cans of beans meet a single criteria, this can be a great solution.  This would be like putting up a sign in Costco that said “Green label farmhouse pictured canned beans, $2.50, aisle 3, 265 cans in stock”.  If you saw that sign, you would get an answer quickly.  It should, however, be obvious why stores like Costco don’t create these particular signs.  If Costco wanted to answer all potential questions, whatever they might happen to be, they would have to place a tremendous number of signs all over the place.  In fact, they would need an infinite number of signs if they wanted to be ready with a quick answer to any possible question.  Clearly this isn’t a practical solution, and we’re left with generic signs like “Canned Vegetables” and long search times for specific questions.  This situation is analogous to using traditional databases to ask sophisticated questions of large data sets. 

To give a practical healthcare data example, consider the following question: “How long does it take to find out how many cardiologists practice in California, and in the last 30 days have visited our brand website, signed up for our speaker program event, were delivered samples of our latest product, and have increased Rx market share in the last 90 days?”  We want to know this so that we can invite them to an exclusive KOL program. Assuming we’re using a traditional relational database, which of the following do you think is the right answer?:

(A) Several hours

(B) A few seconds

(C) Many days

If you answered (B), you would definitely be wrong unless this was the one question you asked all the time.  If you answered (A) you are most correct.   Typical relational queries of a complex nature can take many hours.  If you answered (C), you are partially correct.  There are cases where the data is large and complex enough that the result could take multiple days to come back.  If you need this information for a campaign or campaign adjustment that you want to execute in a hurry, like during a tradeshow, you don’t stand a chance with a traditional relational database.

Luckily, there is a better way.  In the case of finding information about a can of beans, what if we were to deploy multiple people at the same time each solving a part of the problem in parallel?  We would first need to re-arrange the shelves a bit to ensure they are setup in a way that makes it possible for separate people to do general counting on any problem.  Thus, each person would be assigned a collection of products including cans of beans, boxes of cereal, detergents, etc.  They would be given enough information to answer a part of any question asked, but no single person could answer the whole problem by themselves.  When we want to ask a question, we’d broadcast the question to all the people over the intercom.  Each individual would begin counting using the products they have, reporting their answers by holding up a sign.  A single coordinator would be responsible for collecting the held up responses, tallying them, and reporting the final answer to us.  This arrangement would let us get answers to arbitrary questions much faster than the single person approach because each person would answer their question quickly having only to work on a subset of the information.  Even better, we could continue to speed up the process by adding more people to do the counting, breaking up the products into smaller and smaller groupings.

If we replace the word “people” with “computers”, and “products” with “database records”, we can start to see how a fragmented non-relational model for data storage and retrieval makes it possible to get fast answers to difficult questions on large data sets.  With modern, non-relational technology, it is common to deploy many low cost servers each responsible for answering questions on a small portion of a large set of data.  This newer approach makes it possible for brand managers and their service providers to collaborate like never before.  It lets them play with their data first hand and gain insights they never could before.  It reduces costs both in terms of capital and time to get marketing programs delivered.  In short, there is no reason that healthcare marketers should NOT be enabled to properly segment and execute campaigns on the vast sources of data their organization holds.  Data doesn’t win.  Using data to drive marketing objectives wins.  Are you using technology that just slows you down, or does your technology help you win?

At this point, most healthcare and pharma companies are dabbling in online advertising. One source cites that this industry’s spending has reached almost $2 Billion annually, and continues to grow.

Source: eMarketer

However, it is still a small portion of the overall spend at ~5%.  Surprisingly, even the Consumer Packaged Goods (CPG) industry is not spending much more on online advertising as a percentage of total budget, but they do have a reputation for mostly “doing it right.” But why?

Source: eMarketer

       Given the small percentage of online ad spending share in healthcare and pharma, some marketing teams may be tempted to “just get an ad out there” and concentrate too much on the creative.  But what is the marketing objective, or the customer behavior change you want to create?  That is job #1 for the marketer.  In nearly every case, the call to action will have something to do with the respondent reaching into the brand to get more information, to find a doctor, to get a coupon or co-pay discount, etc.

       This touch point, or response, should not just go to a fulfillment vendor or some other isolated data silo.  It should become part of the comprehensive customer database that you use to manage your customer relationships and your campaigns.

Ask your marketing team the following questions about online advertising:

What are the calls to action?

• Do they connect to behavior change in the brand objective?
• If someone responds, where does that data go—and can you see it?
• What happens once someone responds to the call to action in the ad and what is their experience?
• Does your campaign management system get automatically updated with response data and start triggering a special online ad?

       This might sound complicated, but it really isn’t. These are basic questions the entire marketing team should know the answers to.  So, while online ad spend might be a small part of your budget, if you are not using it to create a dialogue with the intent of building an engaging relationship, then that is budget you are probably wasting.

       Online ads can be a low-cost way to gather data, synchronize with your customer database and campaign system, and create loyal customers on your path towards true healthcare relationship marketing.

I’ll boil down these thoughts into 5 tips that should increase the effectiveness of any Relationship Marketing steering committee (Hint: You might want to forward this blog post to your favorite steering committee member if you are already implementing RM at your company.):

Tip #1: Steering committees should include important stakeholders, create their own governance systems, and work as a team. They should be devoid of organizational politics and ideally have between 6-8 members.

Tip #2: Steering committees should clarify and agree on the project’s objectives and ideally produce a detailed scoping document  with the help of subject matter experts. It should include a rough budget, highlight major barriers and risks, and speculate about areas of insufficient knowledge and possible surprises.

Tip #3: Steering committees should decide how to evaluate and motivate the team executing the RM project. They should find a middle ground between micromanaging and dodging tough calls or decisions.

Tip #4: Steering committees should question assumptions throughout the project and translate into business language if possible (i.e. what is the business value of building campaigns towards 20 customer segments versus just 5).

Tip #5: Steering committees need to be able to modify the project’s direction when objectives or opportunities shift. When surprises occur, the best response is to get insight into why.

To read more about the INSEAD working paper, click here. Stay tuned for more information on the upcoming release of The Informed Marketer™: A Roadmap To Successful Relationship Marketing.