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Missing Use Cases key reason for Data and Technology Investments Failure

Ten Building Blocks for an Actionable Marketing Data-Asset – The Avaus Data Factory Part II

Missing Use Cases key reason for Data and Technology Investments Failure

One of the main reasons for failed digital sales & marketing technology initiatives is the lack of proper use case design. Implementing new layers of technology without a well-articulated customer or user need to be solved, is all too easy in the wake of the endless hype cycles that are perpetuated by trusted vendors, advisors and business intelligence providers alike. 

 

In this blog I argue for:

a) How solid use case design provides an antidote to data and technology underperformance

b) How very few use cases or customer journeys need to be re-invented 

c) How B2C and B2B use cases have many similarities

 

This is my second blog post in the series of ten building blocks for an actionable marketing data-asset – the Avaus Data Factory. Without a comprehensive inventory of current use cases, it is not possible to build superior customer experiences based on the Privacy First approach. A current use case inventory to build on is also a prerequisite for innovative future new ones.

At Avaus, we advise clients to start with simple high-value use cases before continuing with more visionary ones. What needs real courage, in my opinion, is to focus on building a robust data capability to implement the really basic use cases that lack both novelty and any element of hype. To make things even easier, we have collected a comprehensive library of use cases that we have implemented over the last 13 years.

 

Fundamentally, most use cases do not significantly differ across companies or industries

 

The creation of a current use case inventory helps a company to solve many complex issues related to data and technology implementations. A use case inventory will almost invariably demonstrate that there are relatively simple solutions to many seemingly daunting business challenges and that marketing & sales tactics do not need to be re-invented over and over again.

The lack of solid use case design is the main culprit for the persistent low data utilisation levels in customer interaction management across Nordic companies, despite years of efforts by marketers, marketing technologists and data scientists.

 

The keys to success in building robust data capabilities are the basics in use case design that normally lack both novelty and the sexy elements of hype.

 

The fundamental idea behind the Avaus Data Factory is to build a capability to collect and combine data from any source. That data is then transformed into actionable user profiles that can be activated in any channel, online or offline. Most importantly, building from day one to enable scalability over time. Avaus does not endorse the “Customer 360” approach, since we only recommend the use of data points that serve a specific purpose, rather than gathering all accessible data into a profile or lake of data. 

To demonstrate the simplification and re-usability of use cases we have divided them into four main categories based on their business purpose:

 

  1. Improve efficiency in marketing
  2. Grow digital (assisted) sales
  3. Increase customer retention
  4. Improve customer experience

 

The Avaus Use Case or Journey Library is a collection of 300+ different standardised journeys and customer communication activities. These are the base for a Data Factory – to be customised for a specific industry, market and client needs. 

*Illustration of use cases in the Avaus Journey Library. They are standardised assets customisable for your business, to be automated at scale.

 

High-value use cases are within these four main categories

Avaus’ approach enables clients to rapidly identify low hanging fruit. The fastest wins are generally efficiency gains. These gains can then be used to fund growth initiatives and should not be seen as cost-cutting business cases. It is not the prioritisation criteria for all our clients but provides a good starting hypothesis. 

 

1. Improve efficiency in marketing

My personal favourite within marketing efficiency is identifying advertising waste to be reallocated for growth. This also minimises reputation damage due to bad or counterproductive re-targeting. Missing 1st party data capabilities lead to a negative customer experience and marketing ROI, wasting budgets on customers for products recently purchased, or totally missing the customer’s mindset and interest.

Many companies have extension rules for customers and prospects to be excluded from traditional one-to-one CRM communications or rules based on recency and frequency. Quick wins can be achieved by applying these same rules to advertising. Iterations of more complex use cases should be addressed only after running out of high-value quick wins. 

Advanced use cases often require advanced predictive modelling of Customer LifeTime Value potential, propensity to buy, channel preferences or advanced bidding algorithms. 

 

2. Grow digital (assisted) sales 

As Covid-19 has dramatically boosted digital sales and services, it is crucial to understand what share of digital growth is circumstantial or contingent, and what is the lasting result of systematic and strategic activities. Covid-19 has impacted customer channel preferences but the answer to what extent, in what segments and for what duration, require improved omnichannel preference analysis for most companies. Digitally assisted sales should be built with analytics and algorithms, based on robust updated channel behaviour understanding, post-Covid-19. 

Avaus library contains a variety of analytical Recommendations Engines, Next Best Actions or Offers, propensity models and price elasticity predictions. Together they constitute a large library of activities and tools for boosting sales across channels. 

 

3. Increase customer retention

In many cases, retention is more significant in growth than in acquisition. Retention is  measured in recency and frequency or stability of the customer base. Customer churn is easy to predict, with a good dataset and basic analytical tools. Preventing churn requires significantly more creativity, innovation and most importantly, understanding the underlying motives of leaving customers. 

Analytic models are quite good at identifying churn sources: bad customer experience related to flaws in customer-facing processes, competitive pressure in pricing, brand positioning being misinterpreted or other business-specific reasons. All of them have different cures. The remedies are most often customer or situation-specific: Increased in-person engagement with the customer, change of price perception with discounts, brand value or CRS messaging, customer services upgrades, benefits and loyalty schemes.

The Avaus 300+ Journey Library hosts a comprehensive shelf of tried and tested measures designed to improve retention in different industries, across several business models.

 

4.Improve customer experience

Short term marketing and sales performance activities and metrics can, in some cases, conflict with sustainable long term value creation and customer experience improvements. Covid-19 has profoundly impacted many customer priorities. Responsibility, trust, individual and customer community support are key topics in marketing strategies of the near future. Use cases should be assessed in the context of Covid-19 triggered non-sales related customer needs and priorities. This will help to build customer trust, loyalty and affinity for the post-pandemic future.

 

From a use case perspective, B2C and B2B cases are surprisingly similar

Decision-making or buying patterns may be more complex in B2B than B2C, but ultimately decisions are made by humans, regardless of the amount of process, data and technology involved. Decisions are always made in a social context – in the B2C context it is friends and family, in the B2B context it is peers, budgets, procurement rules, and organisational structure. In both cases, it is imperative to understand the needs and characteristics of individual decision-makers and influencers interacting within their group and with your company.

The global digital services used by consumers on a daily basis, affect the level of expectation for digital services when consumers use any digital services or switch roles to industrial buyers. Therefore, whether you are in a B2C or B2B context, it’s no longer sufficient to benchmark your customer experience within your industry or competitors. These daily used global services are setting the level of expectations. 

Decisions are, in the end, made by humans, although through a totally different context and processes when looking at consumer and industrial buyers. From a use case design and data requirement perspective, it´s key to keep in mind that dialogue and communication are always designed towards a person. To build meaning dialogue within both industrial and consumer context, it is essential to focus on data points explaining drivers that have impact in decision makers behavior.

 

The key to success in use case design is people-centric data acquisition –  in both B2C and B2B.

 

Having humans at the centre is the key success factor when designing impactful use cases and data capabilities. It is too often neglected as a design principle. It applies equally to both B2C & B2B use cases. In one of my next blog posts, I will address the question: “What customer and marketing data is most valuable in the B2B space?”. 

 

You need a Marketing Data Vision, Strategy and Roadmap to Succeed

Avaus has created a standardised approach for a practical Marketing Data Vision, Strategy and Roadmap to enable improvement of data utilisation in client companies.  The roadmap is the outcome of a 4-6 week project, subject to the availability of our experts and client stakeholders’ time. Take a look at a Customer case study created with the global Stainless Steel Manufacturer Outokumpu and what they have to say about the approach. 

Instead of spending 6+ months on a strategic initiative, this demonstrates the value of execution focus, rather than strategising without a guarantee of specific outcomes. The case does not undervalue the need for company-wide strategy and direction but underscores the need to be pragmatic in the case of data utilisation.

When you start to focus on use case design, it will become clear that you need a good understanding of what data is available today and which needs for tomorrow need to be covered, enabling you to become more data-driven within more digitally focused  sales and marketing. 

 

Keep asking: which business KPI/metric or use case this data point serves?

A good question to ask for each data point to be collected is which use case and business KPI/metric it is serving. Building this kind of business understanding together with your technical and analytical teams will make work more fun from a cross-competence perspective and will also help you to achieve faster better business results. From a management perspective, more attention should be paid to this competence as most organisations make efforts to accelerate their path to digital prowess.

The best inspirations for use case design arise from basic customer behaviour modelling across online and offline channels. In my next post in this series of ten building blocks for an actionable marketing data-asset, I’ll walk you through the principles to enable tying cross-channel behaviour together, from both compliance and technical enabler perspectives. 

AUTHOR

Teemu Relander

Head of Data & Analytics
teemu.relander@avaus.com

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