Part 1/3. Personalisation in depth: enabling the “Amazon retail experience” model for Investment Managers

In a previous white paper, The Digital Transformation of Asset Management: Challenges and Solutions, we identified challenges and provided solutions for Investment Managers responding to digital transformation. In particular, we focused on describing the logical solution architecture to enable a single operating model to serve both traditional and digital distribution channels – whilst serving both to the highest of standards.

In this series of articles we aim to stress test this logical solution architecture by describing how it can enable the Amazon retail experience model for Investment Managers. Such a digital experience is held up as a gold standard and so provides a demanding model to test against.

In this first article: we will outline what the “Amazon retail experience” is; then, we will summarise the key technical challenges this presents and, finally, we will qualify this digital distribution model’s relevance for Investment Managers.

On visiting Amazon, or other large online retailers, it is now expected that you will be presented with a personalised experience. In short, to have the information you want to see, when you want to see it and how you want to see it.

This personalisation is primarily achieved through two mechanisms: one presenting you with what is generally popular, or a current sales focus, and, the other, presenting you with what matches a profile of your past and anticipated interests and behavior.

The first is internal information for the retailer; their inward looking systems can identify what is generally popular, or what they would like to be generally popular, in any particular time frame or market segment. However, it does presume that a structured list of products exists for this sales prioritisation to be matched against.

The second could be described as contextual information, how the customer has reacted, and may react, to a product or service set. It is the “How, where, what and when” of a customer’s behavior and implied interests. This involves building a profile of customer activity and derived interests.

This process can be greatly simplified by having a concrete product set (the characteristics of your product set are fundamentally static or actual “things”). If so, then mutability is, largely, restricted to the profiling side.

Also, if you are primarily selling such product through a single point of sale (such as a retail website) this process of matching a product set to a customer is comparatively straight forward.

It is also simpler if your products are not composite products, if you are not selling within a highly regulated environment and if your market is not highly segmented and served through multiple distribution channels.

Therefore, the challenge of enabling an “Amazon retail experience” is more complex in a highly regulated, highly segmented, multi-channel environment of information based product – the investment management market.

The challenges involve:

• Defining a detailed and comprehensive product set description, at the component level, which can be matched to an equally comprehensive and current customer profile
• A distribution channel agnostic means of creating and maintaining product information, at the component level, to populate and update this product set definition.
• An optimal level of automation to allow this product set information to be responsive and available, at the component level, to be matched with a highly responsive customer profiling mechanism.
• A systematic means of enabling compliance of this product set information, at the component level, across multiple regulatory environments.

These challenges can be further qualified for Investment Managers:

• The “Amazon retail experience” model was designed to facilitate the marketing of tangible products like CDs and books. These products are physical entities and the purchasing process is a transactional process.

• The asset management industry is trying to apply this distribution model to investment products.

• But, an investment product is not a physical entity. When an asset management organisation markets an investment product; it is selling an expectation of an investment return that will be achieved in the future. Furthermore, the purchasing process is not a transactional process because the expectation is delivered over a period of time, which could extend to many years. In investment management therefore, the purchasing process is an on-going relationship process.

• In the marketing process, the organisation must provide 'indicators of confidence' that the expectation will be achieved. And, throughout the lifetime of the relationship 'indicators of progress' towards achievement of the expectation must be provided. These indicators take the form of a set of discrete metrics (e.g. performance returns & risk statistics), and each metric can be provided as at a single point in time or as a historical time series.

These were just a few of the design challenges and qualifications we addressed in the logical solution architecture outlined in the white paper.

The next article in this series will focus on the most mission critical of these challenges: a systematic means of enabling compliance of this product set information, at the component level, across multiple regulatory environments.

In particular, it will elaborate on the “business rules” mechanism within the logical solution architecture. Business rules both allow for systemic regulatory compliance and the means to map contextual information to product set information, and, thus, are at the heart of the logical solution architecture.

The concluding article will revisit the definition and qualification of the challenges an Investment manager faces in enabling an Amazon retail experience and how the logical solution architecture addresses them.