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GPT-3, stable diffusion and web analytics tasks

Tips & Tricks
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GPT-3, stable diffusion and web analytics tasks 1. decision making (decision support) 2. system status message (system health indication) 3. performance feedback 4 Root cause analysis 5. knowledge creation 6. vulnerability assessment 7. prioritization

by Katrin Nebermann

GPT-3, stable diffusion and web analytics tasks

Whether deep learning text or text-to-image generators, the current development of AI projects is impressive. However, the quality of the result depends largely on the prompts and questions. So human intelligence is still required here.

In web analysis, the task or question is also decisive. And it takes data professionals to answer these questions based on the data. Artificial intelligence methods will certainly help with the latter in the future.

Reason enough to take a look at typical questions and tasks in the field of web analytics:

1. decision making (decision support)

Should I offer more videos to increase the conversion rate? Is it true that two-minute videos perform better than longer ones?

2. system status message (system health indication)

Is my conversion rate in the “green zone”? Which KPIs have changed and how?

3. performance feedback

Have I achieved the goal of increasing the conversion rate?

4 Root cause analysis

Why has the conversion rate dropped? Perhaps many new visitors were addressed?

5. knowledge creation

What factors influence the conversion rate?

6. vulnerability assessment

Where do I lose particularly many conversions in the process?

7. prioritization

Should I focus more on the checkout process or the landing pages?

Data analysts will therefore not be replaced by algorithms in the foreseeable future. In fact, the combination of human and artificial intelligence promises even greater added value from the wealth of data. In addition, the level of reporting stands and falls with the database, because the principle of “garbage in, garbage out” (or GIGO for short) applies to deep learning projects as well as web analytics. Distortions in the database are particularly dangerous, for example in artificial intelligence due to discrimination in the data sets, and in web analysis due to consent bias.

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