In the context of IntelligentCX, platform data and content, come in a variety of guises and is invariably the most challenging and most forgotten aspect of any application build. Creativity and innovation typically focuses on features that customers see and interact with, but inevitably data is required in some form or another and is essential to success of most platforms.
Platform Data and Content Needs Assessment
The first step is to ‘bucket’ the platform data and content in to sources. Most data can be categorised fairly easily based on type, where its located and who owns it. For example, data held internally in one database, say transactional data, should be kept separate from a data held in another database, maybe website analytics, each of these data sources will have different owners, processes, requirements for use and need to defined separately.
Description of the data can then be established and once these have all been defined the next step is to get into the detail of each dataset by running through the following steps.
Data or content Source, where is the data coming from is the first question to ask and answer, typically it will sit in 1 of 3 buckets
Internal Data – this is data which has been and is being collected or created by your business, transactional, feedback, behavioral, analytics, inventory, technical, meta, etc. Examples would be technical content created around your products, website traffic stats or purchase transactions such as sales.
External Data – sourced or purchased through suppliers, partners, 3rd parties, etc. there are a multitude of businesses making good money selling data and insight. Examples: contact lists or market insights.
User Data or content – Finally data (content) which you may not have yet which is to be contributed by users through the platform being created. Examples, think Facebook, twitter or linkedIn, data is generated by users as they interact with the platforms, the content they enter and contribute directly and the behavioural data they provide indirectly as they interact with the platform.
What is the Format of the data: there are multiple formats and mechanisms of data format API, csv, excel, txt, database or platform to name but a few. These formats are either static or live, an important consideration is which of these do you need, for example stock data if provided in static form won’t be up to date, as soon as its been generated its considered out of date as stock may have been purchased, as such a live format would be a better approach.
Delivery is intrinsically linked to the Format and considering how the data is to be delivered just as important, example mechanisms for delivery are web services/API, ftp transfer, manual upload interface, etc. again think about the need around the data whether live or static is suitable as delivery mechanisms will need to ensure it matches this requirement.
Frequency, how often does the data need to be updated? As with Format and Delivery, answering this question will help to understand the best approach.
Update Process: how will the data be updated, this is primarily relevant to static data sources and must be understood, although simply stating system to system here for an API approach helps to define the system requirement further along in the platform development. Defining this update process helps to clarify how much effort and resource is needed to support the platform needs and whether it’s feasible or not
Data Owner: this can be an individual’s name, a department, business or end user, defining who owns the platform data and content typically this should define the external/internal owner and who and how they will be responsible for updating the system, but the risks in not doing this part are large, as an example, if the platform data requires updating weekly and takes significant resource to do that update then clearly ensuring ownership and responsibility of this is important. If the department responsible has a team of 2 people administering data yet the platform requires a team of 10 to ensure its suitably up to date for its needs, clearly there is a problem to resolve.
Cost: are there any purchase costs for the data, these costs can be internal resource costs or purchase costs, either way it’s very important to grasps the cost
Effort: guideline of complexity to get and use the data rated from 1 to 10 (10 being the hardest)
The 8 steps above should enable a good grasp of the overall platform data and content needs, requirements and help to obtain feasibility of the project defining how the data can be accessed, how it will be updated, who owns it, etc.
Data is critical to most platforms and there success so ensure you do this exercise early on and comprehensively.
Read on for the 4th step in creating Intelligent Customer Experiences