Ermetica7 | Anna & Andrea | Italy

If you don't like math you can skip this point!Based on our experience in the field of digital services, concerning web design, logo design, brand identity design and white hat SEO, we have calculated the following estimate: 

• 69% of digital services in the logo design, brand identity and SEO sector are low quality and unprofessional.

Note: The 69% was calculated considering that for us "an acceptable and standardized result" is low quality and unprofessional. If you are a professional agency or a freelancer providing quality and professional services, you should not feel offended (you are part of the 31%). Our calculation took into account our subjective side (it was calculated as a mathematical average), our error margin "human bias" (it was calculated and included as a mathematical average). Our calculation is based on several factors, let's define some variables:

• S: Percentage of digital services that are standardized.
• LQ: Percentage of digital services that exhibit low quality.
• LP: Percentage of digital services that demonstrate low professionalism.
• MO: A factor representing the impact of missed opportunities (this is the most subjective).

Let's try to frame it in terms of the probability of encountering a negative experience. If we assume that standardization, low quality, and low professionalism are contributing factors to a negative experience, and missed opportunity is a consequence of these, we could think in terms of sets or overlapping probabilities. We could represent this as: 

• N = (S + LQ + LP + MO_factor)/Total_Considered_Factors
• Perceived_Negative_Impact (%) = f(Standardization, Low_Quality, Low_Professionalism, Missed_Opportunities)

Where 'f' is a function representing our subjective evaluation process. If we assume that standardization, low quality, and low professionalism often go hand-in-hand and lead to missed opportunities, we could think of it as:

• Overall_Negative_Perception = (Weight_S * S) + (Weight_LQ * LQ) + (Weight_LP * LP) + (Weight_MO * MO)

Let's consider if there's any other way for an equation that shows how these negative factors contribute to damage or dissatisfaction.

1. Let D be the Damage (financial, reputational, etc.)
2. Let U be User Unsatisfaction
3. Let F be User Frustration

We could say:

• D = f_D(S, LQ, LP, MO)
• U = f_U(S, LQ, LP) (Missed opportunities might indirectly contribute)
• F = f_F(S, LQ, LP)

These are functional relationships, not direct mathematical equations with quantifiable variables. Let's go with the simplest representation that reflects our calculation based on ours encounters: 

• Total Encounters (TE) = Total number of digital service engagements we experienced.
• Negative Encounters (NE) = Number of engagements they perceived as negative due to standardization, low quality, low professionalism, and resulting missed opportunities. 

Ours calculation can be represented as: 

• (NE / TE) * 100% = 69%

If 69% of logo design, web design, SEO services are low quality and standarized, then 

• the probability of any single service being bad is 0.69, and the probability of it being good is 1 - 0.69 = 0.31.

When choosing between two services, we can think about the probability of encountering at least one low quality service:

• Probability that the first service is bad = 0.69
• Probability that the second service is bad = 0.69
• Probability that both services are good = 0.31 * 0.31 = 0.0961
• Probability that at least one service is bad = 1 - (Probability that both are good) = 1 - 0.0961 = 0.9039 or 90.39%.

So, when choosing between just two services, there's a very high chance (over 90%) that you will encounter at least one unprofessional or low-quality service.

If You don't like Statistics and Probability you can skip this point!  With 10 options, the probability of finding at least one good service increases, but let's look at the risk of encountering bad ones.

• Probability that one specific service is good = 0.31
• Probability that all 10 services are good = 0.31 ^ 10 ≈ 0.0000161 (very low)
• Probability that at least one service is bad = 1 - (Probability that all 10 are good) = 1 - 0.0000161 ≈ 0.9999839 or almost 100%.

If you have 10 options and the failure rate is 69%, you are almost guaranteed to encounter at least one (and likely many more) unprofessional or low-quality services.

1. Think you want someone to help you build with LEGOs. These are like digital services for grown-ups, like making a professional logo or a unique website. 
2. We've looked at lots and lots of these helpers, and it's like if you picked 10 of them, about 7 might not do a very good job. Maybe their drawing is just okay, not very special, or their LEGO building falls apart easily. 
3. Only about 3 out of those 10 might give you something well-made and professional.

So, we think that if you choose someone to help you with your online things, there's a good chance – more than half the time – that what you get might not be the best.

You're really hungry for a delicious pizza. There are lots of different pizza places you could order from. 

1. Some pizza places make amazing pizzas with fresh toppings, cooked perfectly, and made with the correct fermentation time. 
2. But other places might give you a pizza where the crust is burnt, the cheese is low quality, or the dough has not risen with the right proofing time.

Think about all the people who help with online things like making logos or websites. We've looked at many of them, and 

• it's like if you picked 10 different online designers, about 7 of them would be like ordering from a pizza place that often messes up your order or doesn't use good ingredients. You might get a logo that looks cheap, or a website that doesn't work properly. 
• Only about 3 out of those 10 designers would be like finding a really great pizzeria that always makes a perfect pizza.

So, if you're choosing someone online to help you with your business, it's a bit like picking a pizza place. There's a good chance – more often than not – that the 'pizza' (the service you get) might not be very tasty or exactly what you wanted.