Client Strategy: Making Business & Product Strategy Executable

The Missed Step:

Strategy sets the vision, guide rails, and roadmap. But often due to segregation of duties, the application and execution is owned by a different group of people. Good strategies fail because the tactics are often not defined, the right people not informed or held accountable, AND the right clients not targeted.?

The approach to client strategy, (aligning client need to resource), is the key step most often skipped, or executed poorly, which drives the failure to deliver on a business strategy. Furthermore, a robust approach to client strategy is the bottoms-up activity that ultimately drives a REALISTIC and OBTAINABLE business strategy.?

It is also worth noting that “realistic” and “obtainable” should not be seen as a compromise to a business’s ambitions. After all, if you have done your homework properly, your client strategy should help define how ambitious the business strategy can be.?

Client Strategy Driving Business Strategy:

The annual process of budgeting and strategic planning is often an exercise in aspirational mathematics. You are told the percentage revenue or profit increase required. That’s an accepted and understandable practice in a corporate enterprise – particularly a listed business.?

The friction thereafter comes through the cascade. Normally, it is just a cascade of the same math downwards, maybe with a bit of business input on reasonableness. Bums-on-seats and services businesses may work on a target per head and work upwards from there. Even annuity businesses may start with their base line at year end and then work on how many new clients they can acquire or price inflation they can push for.?

NONE of these really put the client at the centre of the equation and how the target will be achieved. They work on a performance model that focuses on individuals as parts of teams being held accountable.?

The question is not:

“how much money do you think you can make?”?

… BUT?

“who are the clients you are going to grow, and how are you going to grow it?”

This approach allows for a much more realistic and obtainable target and budgeting process. People, clients and activities are defined.?

If client strategy is entrenched, then budgeting and business strategy planning become interlinked to the client growth plans.?

The 5 key activities to inform an effective client strategy:

Objectives:

This connects the business goals to how they translate into client activity. The objective maybe to acquire clients, maintain important clients, grow revenue, maximise profit etc. It CAN be all-the-above because that’s the point of segments and service levels. Client strategy by its nature is not trying to solve for a one-size-fits-all approach.

Service levels:

Define the types of service, client engagement or products to be targeted at different groups of clients or segments. This can be high level initially and linked to the inputs, (type of service provided), vs. the outputs, (expected outcomes).

When linked to objective-based statements such as: “Clients we cannot afford to lose”, “clients we need to grow”, “clients we need to service profitably”, you can then align the type of effort, resources and services to be provided.

Often, you will hear service levels given titles like: Platinum, Gold, Silver, and Bronze.?

Segmentation:

This is a data driven exercise to understand client behaviour, inputs, and correlated outcomes. It is the base plate of a client strategy and therefore we will do a deep dive below.

Execution:

Post segmentation you can make informed decisions to refine service levels and execute client engagement. This is the action part but focused on precise actions and specific targets. As the segmentation analysis and performance monitoring become entrenched the service levels become more tailored with a clearer understanding of triggers, input, and outputs.

Performance Monitoring:

Track the activity, which if done properly, effectively becomes the maintenance of segments and service levels.?

The key with the above workflow is it is a journey, spending time on getting it right, right away, is a needless endeavour. This process improves over time, the inputs captured build a clearer picture of the outputs generated.

Segmentation:

Segmentation is a data and analytics exercise which accounts for the bulk of the preparatory work. It drives an effective client strategy and thereafter sets the tracking for performance monitoring – the process aligns client need to a particular objective and approach.

It is often an exercise overlooked BUT occasionally embraced so enthusiastically that it becomes a paralysing exercise in procrastination. To avoid this, businesses need to align the maturity of their business and client base to their Go-To-Market (GTM) approach.

This exercise is normally part of the objective setting process. For example, if a business is starting out, there is no harm ‘throwing whatever you can at the wall and seeing what sticks’. However, it is important to at least understand why and collect as much evidence (data) on the approach taken as possible.

For reference, my experience is centred on Financial Services – so, very mature businesses, very mature clients, and with a significant amount of data already captured. Regardless, the process can be implemented on a relative basis and is easily transposed to different industries or sectors.

Guide rails on Segmentation:

Segmentation is a data driven exercise to understand clients, find successful patterns, align them to other clients and replicate them. While it should be fundamentally empirical, we should acknowledge there is a fair amount of “art” and subjectivity involved.

The risk is a business can over index on the exercise itself. The truth is, like with most data exercises; no amount of data and analytics guarantees future results.

Below are some guide rails to consider while undertaking a segmentation exercise:

Always be mindful of the data source:

“Shit-in-Shit-Out” (SISO) is often muttered in data conversations. It reflects a healthy scepticism on all data-born exercises, and it is where the art comes into the process. Without getting into the weeds of how to build a robust and self-perpetuating data strategy, it is always best to approach segmentation as a reoccurring process. If you are mindful, you can evolve said process to continually improve.

Appreciate Bias:

People look at data with an agenda. Users will always seek data that is self-affirming:?

“Does it tell the story I want or need?”

If not, the scepticism and scrutiny increase. Also be aware of data derived directly from the client. Do they have an agenda to drive in their feedback?

Be Action Oriented:

Focus on analysis that drive actions. Do not make data analytics an academic exercise to solve for a small margin of error. Proof points are clearly measured in outcomes, so focus on the outcomes and adapt.

Repeatable success:

Power comes through data and thus it is occasionally coveted by power hungry data managers. Finding repeatable success is the desired outcome. Importantly it comes through sharing the learnings to empower others.

Opportunity AND performance monitoring:

“Bean counters” are not seen as adding value because the focus is historical, and governance based. Client strategy successfully executed helps client facing staff to be successful, the performance monitoring comes after the win, NOT before it.

Note on Data Strategies:

There is a lot written about data strategies; the governance, collection / ingestion, the operations of data cleaning and organization and the availability / accessibility of data… It is the devil’s work and normally requires a data architecture graphic.

The below list looks at the organization of data sets to inform a segmentation process, rather than concern itself on whether the data is captured and warehoused in a Client Relationship Management (CRM) system, financial accounting / order management software, an Excel spreadsheet, or more-than-likely, a mix of all the above.

The below is not exhaustive and, as above, should be adapted based on business maturity.

Importantly, there is also a fair amount of inference that can be added to the data sets to help enrich and provide more advanced client insights. Often it is the categorization and internal tags that become more important to understanding a broad-based client strategy over time. There is no harm in categorizing by arbitrary perception to start to drive insights - which can then be tested and proven over time.

Generating Insights:

Step 1 - Start with client outcomes:

Capture historic revenues gained by clients - preferably broken down to the product or service provided, when they bought it, and the internal person linked to the account.

Tags that can be inferred or added:

• Categorize the client market demographics.

For example: by geography, size, perceived importance, complexity, and risk

• Categorize the product and services.

For example: the type of client engagement required, the complexity to deliver, perceived importance and sophistication. You may also infer profitability through the above.

• Categorize the individual client teams.

For example: Seniority, geography, role-type. If you want to get sophisticated, you can also start to tag mind-set and type of coverage.

What can be derived from this?

Simple Insights:

• Relative importance of the client, what they are buying, how often, and who are the individuals responsible.

Advanced Insights:

• The inferred tags allow for better pattern recognition across geography, sectors, and client types. This can be correlated to what types of products or services different clients have a propensity to buy, and the type of coverage that drives it. It provides an appreciation for the delivery effort required post the sale.

What this gets you?

This is the basis for your segmentation. It allows an understanding of relative client importance, which can then be tagged to an understanding of the input required.

From here you can start to drive repeatable success across these segments.

Step 2 - Look at activities:

Understand the different actions that were taken. Again, you can start to tag different types of interactions, and this will be part of the service-levels. Depending on your business model, particularly if you are a SaaS or product-based business, capturing data here should be core to how you evolve the user-experience.

Proactive – What did you do?

Calls, emails, meetings. How have your distribution (sales, customer success, relationship management, marketing) connected with the client? You are collecting push-orientated activities.

These are vital data points but should also at times be taken with a dose of scepticism. I’ve yet to see a free-fill text box in a CRM that doesn’t lean towards the positive. You should also be mindful that spam is spam, voicemails are the verbal equivalent. In an ideal world you would want to track documents opens, responses to emails, calls that were answered. Track it all but weight accordingly.

Passive - What is the client doing?

Digital is a powerful tool here. Giving the clients the ability to navigate and access the information themselves. How long were they on the site? How frequently did they log-on? What did they navigate to? What question did they ask in the search bar?

All this information collected and analysed, particularly if across a large client base, becomes powerful data exhaust. Indeed, it can become alternative data that you recycle to drive proactive engagement or help drive deeper navigation. “People also viewed this” or “Top 10 questions” asked is great proactive fodder to push on clients.

Correlate to outcomes:

Activities are great but in isolation they are productivity metrics. They need to be correlated to outcomes.

What this gets you?

Repeatable success. Your activities are the inputs. The outcomes are what they buy. If the exercise is done properly, we can identify activities, to be targeted at types of clients, by specific people, and with an understanding of the expected outcome.

Step 3 - Understand the context:

It is worth noting here that if you understand inputs and outcomes and can replicate them more broadly – you have achieved your objective.

Everything else written below is non-essential or potentially a “nice-to-have”.

BUT depending on your business, and should you go further, you can start to link context to input and output and potentially augment distribution efforts.

Market context:

If you are considering why a client bought something and tracking your activities or customer experience; you are focused on the things that are in your control. However, sometimes we capture money because of the inherent value we provide, NOT because of anything we have done to push it.

In fact, the perfect business model is one where clients consume and pay for value with little-to-no-need to be convinced to do so.

However, if you are really obsessed with repeatable success, bringing in the broader market context (what happened in the market to drive that action), can be a very powerful signal to track.

In financial markets it allows you to look at market dynamics and then focus activities to those clients that have previously traded in similar markets. In a retail business it maybe that one of the Kardashians has posted something on X / Twitter. To really push market connections… it maybe that Kim Kardashian has posted something on Twitter (about Snap let’s say), that might be the signal to a sales trader to tell a portfolio manager to sell the Snap stock.

Regardless of the subject – market movements, what happened in the news, the market data at the time are all powerful ways to target a client if you have the information on what they did previously. Couple that data to what activity you did to draw their attention to the market context, and you have a winning formula.

Personas:

Personalities and how individuals behave may be getting into the dark art of psychometrics and neuroscience, but again they can be powerful insights into how to match personalities with the type of service they require. For example, your most aggressive salesperson is always going to fail if they are targeting a passive user that just wants to consume.

In high-touch sales, it may be hard to convince your customers to take psychological assessments, so this exercise becomes much more of an art through trial and error, and our innate human intuition to understand if we are adding value or annoying a client.

BUT for more digital driven engagement there are tools that look at page scrolling, time on page, speed of reactions, and through this data you can build the appropriate user experience and service model.

What this gets you?

A deep understanding of buyer behaviour, that when correlated to activities and outcomes gets you to a forensic world of sales. If you automate this process – technically client segments become irrelevant because every client can have their own bespoke service plan. It’s just how you augment the process (see the future of client strategy).

Step 4 - Include the client (but beware):

As mentioned, psychometric assessments of your clients might be a step too far, BUT you can always ask your clients what they value?

“Voice of the client” exercises are often undertaken and much like “voice of the employee” or engagement surveys they occasionally provide interesting feedback. The important point of these exercises is to understand how to modify a service or transaction. Finding the tactical actions to influence is more important than the essay you might end up receiving.

These exercises should also come with a health warning. This information will always be biased; either by the relationship that exists, or the agenda a client is trying to drive.

If these surveys are repeated, over time you gain a rich and powerful data set on buyer trends and preferences.

Step 5 – Involve third parties:

There is an incredible amount of content providers and alternative data companies. A third-party maybe the best way to mitigate the bias and scepticism on client strategy, and therefore some may choose to engage third parties straight away.

Noting my own bias, this information provides a powerful outside in data set that can help monitor progress, highlight opportunities, build out a fuller picture on the influence of service models, and the type of product and associated cost that might come with it.

However, it also needs to be incubated appropriately and therefore should not be seen as a completely outsourced approach to client strategy.

Client Strategy in the Future.

All the above is a workflow or process, driven by data.

A lot has been written about GenAI and its impact. Client strategy is an obvious use-case. I’ve written about this for quite some time.

Client strategy can be linked up to an Amazon ALEXA, there are also early versions of natural language models applied to the above data sets. There are chat bots that you can ask what the right activity is to drive client engagement, and there are alert systems that flag when an activity is required.

If you work in sales, imagine being able to wake up and ask the question:

“Who is the best person I should speak to today? About what? And what would be the outcome?”

Client strategy is the exercise that drives the business strategy. If you get the foundations right, it can be augmented so that you make your salesforce bionic.

All GenAI use cases are a journey and so is client strategy… there is value regardless of how you choose to use it.

Views are my own and not necessarily reflected of any of my previous employers.