Personalization and CDP
Personalization
S. Ernest Paul | Shutterstock
S. Ernest Paul | Shutterstock

Brands have to identify and understand each and every customer 

Ever been to a restaurant where they know you by name? and the waiter happens to know your preferred drink of choice and like magic brings it to your table while you are getting seated. The ‘Cheers’ kind of experience for those of us who recall the sitcom. These one-on-one personable interactions make experiences special.

We live in a digital world now and demand similar experiences from brands. We want to associate with a brand who knows us. We gravitate towards these brands, rare as they might be. However such a rendezvous brings familiarity & comfort. Trust soon follows. I recently called up my banking institution over the phone, a few taps on the phone initiated by me and there was a friendly voice greeting me personally instantly. Voila! All done with voice print. We expect similar experiences, minimalist, natural, efficient and transferable across devices.

"Patience in today's hyper connected world is on a diet due to clumsy marketing tactics"

What do customers want from brands?

On occasions while dining I have often witnessed all individuals seated at a table nearby simultaneously glued to their mobile phones. Digital and mobile may have taken us all by storm long ago but we do seem to prefer company even if it of the silent variety. This mobile solitude may be amusing to some, not marketers. To marketers, this means real time location data, related contextual information including weather, possibly to trigger a nearby physical store location reminder.

Customers want relevant, meaningful and tailored information and offers from brands who meet their specific needs. Irrelevant offers and emails induce customer paralysis and prove to be counterproductive. In this era of instant gratification and attention span deficit, there is little room for off target customer communications. With a thorough understanding of customer needs, both parties are likely to benefit.

Customers have long declared their expectations. See Figure below:

Delivering on customer expectations enhances customer engagement leading to loyalty for brands, resulting in reduced acquisition costs, a revenue upside and increased retention rates.

The journey begins with data

Brands seeking customer-centric nirvana have to become data-centric, first. None of this degree of hyper-personalization at scale can be accomplished without customer data.

"Data is the new oil. Refining or anticipating customer needs is the beginning of personalization"

This crude oil or rich behavioral customer data, customer interactions, social media activity, demographics, customer life cycle stage recognition and transactional data can be segmented and further sub-segmented. Personalization dividends can be harnessed today without a full blown implementation of technology such as a Customer Data Platform, a CDP. Existing data can be used in cross-sell initiatives, enablement & activation of a few consumer use-cases based on past purchases and behavior. Sometimes using less data is more effective prior to incorporating external purchased data sets.

Incorporation of 2nd & 3rd party external data adds dimensional layers to the refinement process and further enriches customer data. Multiple digital identities, which many consumers use online can be merged into a single record to eliminate redundancy. Iterative cycles of customer behavior and interactions captured via analytics continually refine customer data. Behavior solidarity within customer ‘data sets’ feeds pattern discovery and recognition. With confirmation and accuracy of patterns, machine learning kicks the ‘data sets’ up a notch. With continuous cycles of deep learning & artificial intelligencepredictive analytics begin to unlock future customer behavior. 

How far along is your organization in channeling this new oil, 
piping it, refining it, triaging it, harnessing it to extract
measurable value?

Agile, cross functional teams – marketing, tech experts & operations must work together

Working in silos is kryptonite for personalization. Having a cross functional team in a test and learn mode, sharing insights within a ‘not afraid to fail culture‘ is the best environment to productively deliver, preferably in a war room like setting.

The personalization DNA resides in behavioral data. Its application rests on a thorough mapping and intersection of customer journeys, triggers, devices, events, marketing campaigns and collateral aligned to customer segments with matching behavior. A cross functional team serves this proposition well.

Marketing & Operations realignment

Organizations must look at the personalization ecosystem in its entirety, from data manage­ment to advanced analytics to customer en­gagement, through to measure­ment and optimization. Marketing resources are generally organized by specific skill. For example: Analytics or Campaign management or even by Chan­nel – Social or Search. There is an unintentional siloed ecosystem risk to be wary of. Although optimizing for different elements is import­ant, the whole is greater than the sum of its parts. An understanding of how the different parts interact and how to inte­grate them to support personalization is what differentiates high-performing marketing organizations from poorly performing ones.

Building the customer journey

Grouping customers together with matching needs and behavior is a good place to begin. Armed with a handful of these groupings or segments, align each segment with its own customer journey & map the series of interactions with the company brand. Examples: Visits to a broker, agent, company website, calls to a call center, social media posts, even tracking prospect visits to the company brand’s competitor, etc.

Building customer segments

Hundreds of mini-segments may emerge as a result of combining journeys and customer segments. Each mini-segment may be nuanced and one more valuable than the other. Each should be considered & prioritized by its relative value. For example: Consider a leading insurer who may find it more valuable to engage with its customers who are within their ‘renewal window’ by sending them a reminder that their policy is nearing expiration. Rather than pushing them towards a cross-sell product and risk losing the customer to a competitor, the insurer chooses to send a limited-time policy renewal loyalty-offer.

Harnessing customer signals

The customer provides signals as to their intent with their online & offline interactions. Mature predictive analytics catch these signals and push them into a workflow to be followed up by an appropriate response. Each signal, nevertheless deserves a response, a timely and relevant trigger message, to close the loop.

Signals & Triggers at work

With advanced and meticulous planning, a library of signals and matching triggers have to be maintained and kept up to date. Each trigger with matching collateral can then be dynamically executed. Each of these combinations are continually refined & optimized by analytics. Upon a valid declaration, each becomes a business rule. For example: Consider a leading health insurer who learns of a dependent soon to be in the ‘dependent turning 26 window‘. The customer and/or dependent promptly receives a triggered message with a limited time offer towards a new personal health insurance policy for the dependent.

Pharma & Life sciences regulatory caution is giving way to customer personalization

Regulated industries in Pharma, Life Sciences, Healthcare and others have been increasing personalization related spend. Even with an innate regulatory driven caution, the portfolio trajectory is shifting from clinical trials customer data spend to customer/patient experience related personalization spend.

Customer data & personalization together aid in the identification of high-value patients, who can then be channeled towards physicians and therapists, realizing a tailored & personalized formulary experience

Insurers have personalization high on their portfolio spend agenda

Insurers are attaining underwriting efficiencies, realizing a not so far off dream of instant insurance for Health, Life and others. They are now providing customers Population health efficiencies and Genomics focused underwriting, all a result of data personalization. The race is on and competition is rife. Personalized internal & external customer data, including IoT customer data can now reside within a CDP or a similar configuration.

Stitching the Personalization DNA within your marketing technology stack or with an addition of a CDP

Achieving growth on a large scale, across all channels and geography requires immense preparation, alignment, governance and most of all leadership and talented human capital. 

Rerouting existing operational organizational alignment, restitching operational processes and RPA driven workflows, scaling across the company incrementally and globally requires a well-articulated blueprint with an equally agile playbook.

New marketing technology configurations equipped with a ‘smart brain‘, ready to direct traffic with rules & algorithms, can finally foster a new breed of a one-to-one marketing reality.

Avoiding pitfalls and traps

A series of steps may be necessary to arm an incumbent MarTech stack to minimize ROI leakage from new technology investments.

It is easy to rack up a bill in the millions on data integra­tions that magnetically pull all this information together into a data lake, prioritizing the most valuable types of data—the kind which drive the high value use cases. Identification of the required latency for each data element is critical at this juncture. Most use cases require real-time information for a limited set of data elements, so most real-time capability can be thankfully decelerated.

Discover business use cases which the technology would drive, not vice versa

Buttressed by an agile development process formulate business use cases supported by KPIsbusiness drivers and forecasts. Existing digital analytics would aid in benchmarking, revealing delta variances and future forecasting. The market­ing process is iterative, optimized and improved with each cycle. 

Collaborate closely with the Marketing teams to uncover functional requirements

In close collaboration with the marketing operations team, functional requirements must be well articulated and documented. Juxtaposed against the numerous technology solutions & providers which make up the MarTech landscape, this step is a cornerstone effort. Multiple use cases, storyboards or multiple contexts help in identifying a certain missing technology component. This good catch may lead you to a different vendor choice and selection when augmenting your technology to fit your personalization goals.

Align organizational needs and goals with a technology approach

Major integrated Marketing Cloud suite vendors including Oracle, Adobe and Salesforce do not support the personalization ecosystem end-to-end. Brands may already have one of these suites in place. In that case, a reasonable compromise would be to extend the capability of the existing suite with the best of breed of each functionality element missing from the existing MarTech stack. The downside would be a less than tight integration to the element supporting that specific functionality or service.

A key consideration for the analytics engine – The analytics engine ‘the brain ‘ should be customizable including the algo­rithms, data features and business rules specific to your requirements. The solution set should allow you control over the inputs to the analytics engine.

Build incrementally and via pilots 

A prudent approach would be to set your sights on an iterative and incremental value delivery approach supported by well-defined pilots. With each new element added for a new use case, costs rise.

However, the incremental value attained would likely align with the incremental investment, thus justifying the investment. A phase driven and stage-gated approach would smoothen the decision making for the CFO to fund the incremental spend.

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