Build an authentic customer business model that works

What is Customer Authenticity?

How good do you think your customer’s experience really is?  In a ‘complex’ sales process there are many different stakeholders, constituencies and offerings and ways to engage.  Bill Schmarzo reminds me that customers are not buying your product, they are buying a means to making better business decisions.  The more efficient and pleasing you can make this experience for them, the bigger revenue multiplier your customer functions become for you.

Given the number of variations, inflection points and influences in each account – and therefore the number of different customer functions you establish to engage with them – dynamic ‘micro’ business models effectively co-exist, by function, within the hierarchy of the overall customer business model.  In an overtly political organization these become mini fiefdoms of control.

Over the length and complexity of a customer journey, Customer Service, for instance, has its own discrete business model separate from social communities or marketing events.  There are Sales and Customer Success goals.  Discrete customer functions are likely also to differ and depend on nature of customer segment, the customer audience involved, the context of the engagement, the level of communication between individuals on the customer side and the specific customer journey within that segment.

Customer Authenticity is described as the coming together of humanness, emotional intelligence and customer satisfaction.  Your customer encounters all of the functions in your company that include the word ‘Customer-‘ during their journey with you. Your responsibility is to design it well.

 

Customer Framework

With the large number of moving parts, you can’t expect one method or set of tools to work for every situation a customer encounters.  What’s needed is a framework for getting things done, so that definitions and measurements can be compared and aligned and made actionable in a dynamic way, while remaining lean and focused.  The conversation then shifts from ‘complexity’ to ‘design’, where the variables are considered as:

1. design constraints that help us map out…
2. the scope of the algorithm required for simplifying and improving the overall customer experience.

Designers talk about the knowledge funnel, the progression from 1) an unknown to 2) a strong hunch (the ‘heuristic’) to 3) knowledge, to 4) an algorithm and onto 5) code.  Modern companies have all the necessary resources to bring these together, they just need to do it.  This is a complex but feasible task using design processes, data analysis and AI.  In the long run it may actually be more cost-effective to design and plan for this than not.

The first thing to do is to untangle the ball of string and consider the drivers.  I’m a fan of the rule of three, so here are three good cross-referencing perspectives to start with:

Matt Ehrlichman gives a nice overview of ‘The 8 Principles of Customer Delight‘ while few large companies design their business for customer delight as well as Intuit (‘D4D’ Lab), as showcased here.  What I want to explore in this blog post more specifically, is a business model framework for pulling together the operations needed to delight every customer in a dynamic, high volume business, every time using all the tricks in your toolbox.  If you like a short read, don’t go beyond the graphic!  If you’ve got a few more minutes, I go into some specific details below.

With that, here are seven operational components for building a ‘delightful’ customer experience:

 

1. The Circular Business Model

Most effective – customer segments and markets are dynamic and differ in scale and nature. Use Business Model design to determine most effective method of working with customers based on the customer segment. The goal is consistency and predictability – where behavior is dynamic, consistent process is increasingly important.  A circular business model will sustain your customer relationships and your business by careful management and growth through multiple, iterative purchasing cycles.

 

2. Managing Customer Segments

Observe what defines a customer segment and then for each, consider:

• Audience – there will be multiple, at different levels, within a vertical, or an industry. Who are you supporting?  How do they influence each other?  Are your marketing to a single customer or the entire segment?  Determine who’s challenges you are solving for.
• Context – what is your Value Proposition and to whom? Context matters.
• Story – how do you make the emotional connection? Storytelling is critical.

For high touch customers – determine their constraints, scope, objectives etc. and co-design with them.

For low touch customers – prototype and test concepts rapidly test-regions within this market.

For long-tail customers – design for dynamic interaction of customer functions to deliver ‘authentic’ experience without direct personal engagement.  Consider your customer ‘promise’ and the level of ‘authenticity’ that the engagement provides and the ‘feeling’ generated after an interaction.

Complex projects should be designed as a Service using Service Design processes to achieve efficient utilization of resources, higher productivity and outcome objectives.

 

3. Customer Outcomes

Outside-In is the only way to design for authentic customer engagement and experiences and in turn drive your own business goals.  The closer your outcome objectives align with your customer value, the easier and more dynamic the whole system becomes to manage.

Customer Co-Design.  Understand the decisions customers are trying to make in each segment (hint: it’s not about your product, it’s what your product enables them to do).  Design for them and with them.  Don’t rely on data alone.  If high-touch engagements can’t be justified for sales value alone, reframe them as co-design opportunities with your customer segments.  Put time into the design process and take the rich insight that real people provide.  As referenced here, you don’t need to talk to many customers to gain reliable insight.  Use analytics to spot repeat patterns and drive new insights and opportunities, spot risks and fill gaps.  Use AI to make predictions and model against historical analysis.

The high touch > low touch > technology markets.  Have a small number of high-touch engagements within each of your segments and markets.

Customer Relationship > Acquisition, Renewal or Up-sell – how do you design for each of these and what are your engagement models?  What are your customer advocates telling you and what is your data telling you?  How can you automate the dynamic interaction of your customer functions to support any one of the inordinate number of continuous customer interactions that take place?

Designing with customers does not mean engaging a focus group to give you feedback on what you’ve already got.  ‘Design’ means entering an ideation and discovery process, observing activity and behavior and attempting to determine the most logical explanations.  There are no benchmarks or handholds here, this is the raw exploration of emerging scenarios.

 

4. Dynamic Customer Journey Models

Do you know what makes your customer your customer?  Or why your non-customers are non-customers?

You likely have several customer touch-points and programs around advisory, advocacy, communities.  How well aligned are they?  What is their overall strategic value to the company, how are they defined and how are they measured? (hint: it should be a hierarchical model that satisfies your company’s vision, mission and outcome objectives).  Here are some key questions to ask:

• Is your customer’s journey interrupted? What is the outcome impact of this?
• Are your customer engagements designed to sell (inside > out) or to help (outside-in)?
• How well do your functions align? Is your organization or point of view a problem?
• Where do the creative sparks for your products and product marketing come from?

Have you determined how high-touch engagements can inform low-touch engagements and improve their outcome?  Or how High- and low-touch engagements can influence the technology-based long-tail of your business model?

What if your Net Promoter Score is great! – but you’re not growing?  See what Intuit did by using design and data to innovate and grow with already seemingly satisfied customers.

Yes, it’s a complex world out there of continuous customer interactions:

• It is complex – with multiple channels and influences in each channel, where constant innovation in acquisitions and renewals is required;
• It is dynamic – emotion and influence exist throughout the buying cycle, and it can often appear random and unpredictable. Sales and Marketing Ops data, analysis and AI can step in here to identify patterns and model for specific customer objectives and customer propensities that satisfy company outcomes.
• Loop-Back – it can appear that the funnel has no obvious entry point or conclusion that you can control – and maybe ‘control’ is the first thing to let go of. You can reframe the ‘loop’ as a dynamic and circular business model driven by excellent customer experience, which data analysis and AI will help you define, measure and drive.

The purpose of your business model is to create a lean, efficient revenue model for the business that has customer value at its core.  Any internal activity or resource utilization that is not efficient in its support of customer value is just getting in the way of the business objectives.

 

5. Collaborative Customer Functions: Service Design

Draw a Service Design map across your customer journey and the functions a customer engages with across their entire journey.  How contiguous or just good is the Service Design?  Are the services dynamic?

Design preferred interaction models by customer segment, showing what the preferred workflow of interactions and services actually looks like.  Design rapidly with real customers, test in low-touch and technology environments using Business Design, Service Design and Design Sprints.

Where is the data?  You have to think laterally here – who in your organization has the data that is most relevant to your function?  It is likely that it is not in your BU.  What level of forensic detail can you go to and who are your ‘radical collaborators’?  You’ll find a treasure trove of cross-referenceable insight by engaging collaborators from Sales Ops, who are focused on mapping from hunches to revenue, and Marketing Ops, who score the effectiveness of marketing initiatives.  Get their data into a visual 3 dimensional customer model and sit back.

Achieving Scale

How to observe?  Interview stakeholders, from different customer engagement functions at key points across the journey, including: sales, marketing, services, customer success and customer service, your EBC etc.

How to design?  Consider a use-case where significant incremental impact can be made without cost.  Facilitate a team to design for net new opportunity = limit risk, opportunity for significant impact

At little or $0 Cost?  Initial driver to stakeholders can be revenue growth by increasing efficiency and productivity from existing resources and activities

Engage Customers to co-design.  Customers regularly provide insight at high-touch points along the journey.  Co-design with them here with agreed objectives (e.g. using EBCs for co-innovation); prototype and test results through data analysis (sales ops) or ‘Shark Weeks’.  Scale out from high-touch (enterprise) to low-touch (SMB) to tech-only (long-tail) environments.  If you’re really cool, do this.

 

6. Design, Data and AI

Ok, this section should be obvious.

Design – design a business your customers will love.  That means every interaction with your customers is of value to them.

Data – your business is awash with data that you are already analyzing for patterns from which you can deduce all sorts of customer insights and propensities.  Data analytics is pure gold for designing awesome customer engagements.

AI – AI is all the rage right now.  It’s light weight and smart – if you use it to be predictive.  Here’s the thing:  design and AI share a common root in engineering and a common logic which is known as ‘abductive reasoning’.  Abductive is different than deductive reasoning, because while deductive reasoning allows us to deduce likelihoods from known data – the number one use case for analytics – the abductive allows to ask, “how might we?” so that we can be predictive.  This is the method for turning an unknown into a heuristic, that I referenced in this post.

The most important point here is this:  don’t waste all that brilliant AI intelligence to further query what you already know, use it to make bold predictions and rapid iterations.  Put the AI in the hand of your designers.

The premise is that whatever you design for, can be tested for feasibility and viability by identifying patters in data.  Big Data is good for identifying patterns and propensity, but is compute-heavy.  Machine-learning/ AI, on the other hand, follows a very compatible and similar 5-step design process as design thinking, with a light code and data footprint – it is effectively a digital observer that can be trained to predict based on the outcomes of the phases of your design workshops.

• Big Data confirms Patterns and is deductive. It requires heavy compute power, but is in widespread use and prevalent in most companies.
• AI enables prediction, maps 100% to Design process (“how might we”) and is abductive. AI is surprisingly lightweight in terms of coding and compute power needed.

 

7. Customer Success, Everywhere

Customer Success Management (CSM) functions point the way forward for every customer authentic business model.  This is the framework.  Designed to maximize customer contract value, reduce churn, grow renewals and up-sale, CSM functions deploy a high degree of Sales Ops forensics to deduce the opportunities for maximum revenue outcomes through a lens of great customer experience.  Championed by companies like Salesforce and Gainsight, it is most prevalent in subscription-based, SaaS companies.  There’s no reason it can’t be applied in every business case that involves customers.

Customer Success Management:

• Optimizes via Deduction – CSM is about looking in the rearview mirror and optimizing. It has a fundamental CX orientation at its core.
• Should be a customer design stronghold – Deployed to co-design and innovate with customers, it will fully enable the authentic and circular customer business model. There is a strong opportunity and logic for doing so, as CSM has a track record of designing blueprint for downstream selling best practices.

 

Conclusion

My favorite customer quote ever is this:

“Everything between me and your engineering team is shit.  Your engineers are awesome.”

It was an immensely valuable lesson in advocating for an outside-in design for customer experiences,  delivering products and value in a simple, uninterrupted way.  These days, companies have no excuse for letting complexity become a problem.  Modern companies have all the necessary resources to bring these together, they just need to do it.  This is a complex but feasible task using design processes, data analysis and AI.

Like Intuit did, start small to prove a minimum viable approach in one part of the business.  Then use success there to drive a culture of customer delight and authenticity across the business.  In the long run, designing a cost-effective culture of customer success and prediction into every aspect of your company will prove to be your most viable business driver.