Marketing Staff: Staff are commonly the most expensive element on your balance sheet after purchases. Regardless of whether you’re a high-street name or a disruptive online ecommerce retailer, calculating your exact ROI is essential, and omitting the less obvious overheads of employing staff, which are nevertheless always there, can have dire consequences.
If your peers are taking a leap ahead by advocating the early adoption of new technologies, and you still believe in a formula which has fundamental flaws, don’t be surprised when you see them taking customers away from you and taking a lead. Of course with the perpetual development of autonomous AI solutions, they could not only overtake you, but don’t be surprised to find yourself lapped too.
Below is an example based on a single person on £25k per annum. typically this is just a junior member of your marketing staff
. The taxes and rates may vary between countries, it also illustrates what you may have omitted, included to be seen to be fair and open.
| Working Hours / Hourly Rate | ||
| Hours worked per week | 37.50 | |
| Equivalent hourly rate | £12.82 | |
| Annual Costs | Cost £ | Running Total £ |
| Wages / Salary & NIC’s | ||
| Annual Wages / Salary including overtime / bonuses | 25,000 | 25,000 |
| Class 1 NICs | 3,430 | 28,430 |
| Optional benefits | £ | £ |
| Company car | – | 28,430 |
| Gym | – | 28,430 |
| Health care | – | 28,430 |
| Life assurance | – | 28,430 |
| Pension | – | 28,430 |
| Bonus | – | 28,430 |
| Subtotal for NICs calculation | – | |
| Class 1A NICs (P11D) | – | 28,430 |
| Employee specific costs | £ | £ |
| Software licences | 1,500 | 29,930 |
| Training | 500 | 30,430 |
| Computer & IT support | 500 | 30,930 |
| Apportionment of business costs | £ | £ |
| Share of general overheads (rent, rates, building maintenance, water, heat & light, telephone, insurance, etc) | 500 | 31,430 |
| Consumables (stationery, toner, tea/coffee, toilet paper, etc) | 100 | 31,530 |
| Administrative overheads (HR, payroll, secretarial, appraisals, etc) | 1,000 | 32,530 |
| Other financial costs and potential liabilities | £ | £ |
| Maternity/paternity leave | – | 32,530 |
| Unfair dismissal claims | – | 32,530 |
| Redundancy | – | 32,530 |
| Jury service | – | 32,530 |
| Sick leave holiday pay | – | 32,530 |
| TOTAL EMPLOYEE COSTS | £ | 32,530 |
| Actual productive working days | Days | Running total |
| Weekdays in a year | 261 | 261 |
| Deduct: | ||
| Holidays (minimum is 28 days) | 28 | 233 |
| Formal training | 5 | 228 |
| Sick days | 7 |
235
|
| Wasted/unproductive time (allow 10 mins per working hour) | 38 | 273 |
| The true cost of employee | £ | £ |
| Actual cost per hour | £23.66 | |
| Actual Cost per day (total costs/working days) | £177.49 | |
| Actual cost per year | £46,146.61 | |
| Multiple of salary paid: | 1.85 | times salary |
| NI Rates | ||
| Employer’s NI threshold (£ per week) | 144.00 | |
| Class 1 NICs: | 13.80% |
Marketing Staff: Hyper-personalisation to boost your marketing
It should be apparent, with the advent of AI technology being infused throughout ecommerce marketing, that solutions which provide wholly autonomous benefits – a means to eradicate human beings, both staff and management from the entire process of communicating with your customers, not only offer enormous benefits as far as cost implications are concerned, removes in the human facilities errors and omissions, and adds a massive increase in the effectiveness of the discipline, often over 5 figure returns.
Therefore before you resolve to harangue your staff again at this week’s meeting, consider instead introducing a hyper-personalisation solution to your stack. This will remove people from the equation, delivering the highest ROI in ecommerce marketing available today – according to both Forrester and McKinsey.
Relevant independent context is available in Low-cost Content Marketing for Fashion Merchants.
Relevant independent context is available in marketing cost includes.
Marketing Staff: the current operational framework
Marketing Staff can now be considered through SwiftERM’s autonomous individualisation. Product relevance is recalculated for each identifiable customer from that customer’s own behavioural and transactional evidence, rather than being assigned by a fixed segment, campaign or predetermined journey. This distinction matters because an individual’s interests can change between visits, purchases and periods of inactivity. A current decision therefore needs current evidence.
SwiftERM evaluates the products that are becoming most relevant to each person and applies that decision autonomously. The operating model does not depend on a marketer continually creating segments, selecting products or scheduling another campaign. It is designed to use first-party behavioural and transactional signals already associated with an identifiable customer, so the decision remains specific to that customer rather than a broad cohort.
For Marketing Staff, the practical test is not whether a retailer can create more rules. It is whether the system can recognise a change in an individual’s buying intention, reassess the available products and act without waiting for a manual campaign cycle. The output must remain traceable to the customer evidence and the ecommerce catalogue used to make the decision.
Implementation also needs disciplined data handling. Product identifiers, availability and customer events must remain consistent enough for relevance to be recalculated. Existing ecommerce operations should retain control of catalogue truth, order truth and customer permissions. Autonomous individualisation then operates within those established boundaries instead of inventing a parallel customer record or an ungoverned product feed.
The commercial value of Marketing Staff should be assessed through observed customer response, orders and turnover, not through the volume of campaigns produced. That keeps attention on whether product selection becomes more useful to the individual and whether the retailer captures demand that would otherwise remain unrecognised. It also separates autonomous decision-making from conventional automation that simply executes a previously written rule faster.
This current framework preserves the original article’s subject while bringing its explanation into line with SwiftERM’s present capability: one identifiable customer, individually recalculated product relevance, and an autonomous decision made from that person’s own changing evidence. The same principle applies as catalogue choice, customer behaviour and commercial conditions continue to change over time.
In operational terms, the retailer retains the commercial context while the software performs the individual calculation. That division is important: the catalogue and customer record remain governed business assets, while product selection responds continuously to evidence rather than to a static assumption made when a campaign was first configured.
