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Adding Alt Tags to Site Stripe

lyfsy
Feb 26th, 2020
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  1. Adding Alt Tags to Site Stripe
  2. Is this possible?
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  14. I moved everything from hosting on my server to Site Stripe but I presume that means the images do not have alt tags. I have tried to add them but I cannot.
  15. Anyone?
  16. LinkedIn is the perfect platform for this, as executives can have their own profiles and can share content as needed.
  17.  
  18. Because executives have more personal credibility, their link suggestions are much more like to be taken seriously by users than a company profile simply sharing links to their blog.
  19.  
  20. The executive’s profile is “vouching” for the content, making it more trustworthy.
  21.  
  22. When possible, ask executives for their insight or commentary on an article that can then be shared with the link.
  23. Users like hearing the opinions of influential or high profile people, so adding this personal touch can help increase interest.
  24.  
  25. 4. Reach out to the Social Profiles of People Who Are Authorities
  26.  
  27. LinkedIn is great for building personal credibility and sharing content, but you can also use Twitter, forums, and Facebook to do outreach and get others interested in your content.
  28.  
  29. On Twitter (and Instagram), it’s a common practice to follow people in your industry you hope will follow you back.
  30.  
  31. Taking the “first step” toward building a relationship can help get you noticed organically and hopefully start a relationship.
  32.  
  33. After following someone, send them a tweet mentioning something they did recently, such as podcast they were on or an article they wrote.
  34.  
  35. This can show that you admire their work.
  36.  
  37. People are much more likely to take an interest in someone that they know already appreciates what they do – because it doesn’t feel like they have to win them over – it’s already done!
  38.  
  39. A well-structured account.
  40. Correct conversion data.
  41. The correct attribution model (hint: the correct attribution model is not last-click attribution).
  42. Machine Learning Depends on Correct Data
  43.  
  44. Machine learning models are as their name implies, systems that learn how to achieve something.
  45.  
  46. There are different specific approaches to achieving this learning capability. Generally it depends on refining the machine’s decision process when its decision or prediction is not in line with the expected and desired outcome.
  47.  
  48. Let me give a simple example from my days on the Quality Score team at Google.
  49.  
  50. A machine learning model looked at historical data about ad auctions. It looked at all the conditions of a search and the attributes of the ads that were clicked.
  51.  
  52. By comparing these signals, it might have learned that CTR is usually better when the advertiser’s domain corresponds to the location of the person doing a search (e.g., a French user might be drawn more to ads with .fr domains than with .de domains).
  53.  
  54. The machine can learn this because Google has correct data about click-through rates.
  55.  
  56. But what if their CTR data was inaccurate? Then the system might have started to reinforce what the humans who programmed it would consider incorrect decisions.
  57.  
  58. This is the idea of “garbage-in, garbage-out”. It’s the principle that good decisions are dependent on good information.
  59.  
  60. Because machines lack human judgment, they are even more dependent on good data than humans. They can’t easily determine that a prediction that seems statistically sound may simply not hold water in the real world.
  61.  
  62. So how do we give correct data to automations? It all starts with conversion tracking and attribution models.
  63.  
  64. Attribution Models Should Reflect Typical Consumer Journeys
  65.  
  66. Unless a consumer has strong brand loyalty, chances are they will do more than one search before buying something and they will have multiple touch points with a variety of brands during what’s called their customer journey.
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