Recommendation algorithm is a great way to market your products or services based on the activity of a user on the internet. We have all come across recommendation algorithms while surfing the internet, without even knowing much about it. For example, if you had just bought a laptop through an online store, you might have noticed that you keep seeing recommendations to a similar store or to stores that provide complementary products such as laptop bags, etc. These are forms of recommendation algorithms and are a wonderful way to boost your sales and brand awareness. If you know how just to use this strategy, you might see a significant improvement to your sales and brand image in no time.
This course might be of great benefit to marketing and IT professionals, provided that they have a basic knowledge of digital marketing. You will get to identify the sites that have recommendation algorithms, with a thorough comparison between recommendation algorithm vs. SEO. The course will also cover topics such as total engagement, reviews and review quality.
This course will give you access to insightful modules that will guide you on how to influence recommendation algorithms, how to increase your “signals” and how to recommend your products or similar products in websites. The course curriculum will also look into the various ways of advertising that will boost recommendations.
As improvements and advancements are made in technology, online courses are no longer just conventional means of studying at affordable costs. In many aspects, online training offers superiority to traditional learning. There is an effectiveness and convenience that traditional learning cannot provide. The overall convenience and flexibility make it a superior learning method.
1Training offers the most convenient path to gain an internationally recognised qualification that will give you the opportunity to put into practice your skill and expertise in an enterprise or corporate environment. You can study at your own pace at 1Training and you will be provided with all the necessary material, tutorials, qualified course instructor and multiple free resources which include Free CV writing pack, TOTUM Discounted Card, Free career support and course demo to make your learning experience enriching and more rewarding.
The course will be directly delivered to you, and you have 12 months access to the online learning platform from the date you joined the course. The content will be accessible to you 24/7. The course is self-paced and you can complete it in stages, revisiting the lectures at any time.
Those who successfully complete the exam will be awarded the Certificate in Advanced Marketing Using Recommendation Algorithms
The certificate will be awarded by CPD and iAP. This internationally recognised qualification will make your CV standout and encourage employers to see your motivation at expanding your skills and knowledge in the IT enterprise.
On the completion of this course, you will be qualified enough to work for a range of jobs in the marketing industry. This certificate will also help with your career progression by putting you in line to demand for a higher pay or job promotion from your employer. Listed as follows are some of the jobs this certificate will benefit you in, along with the average UK salary per annum according to https://www.payscale.com,
PLEASE NOTE: We do not provide any software with this course.
|1: COURSE INTRODUCTION|
|1.1 Welcome Intro|
|2: SEO VS. RECOMMENDATION ALGORITHMS|
|2.1 The Magic of Recommendation Algorithms|
|2.2 Which Sites Have Recommendation Algorithms|
|2.3 Real Life Example|
|3: HOW TO INFLUENCE RECOMMENDATION ALGORITHMS|
|3.1 What Websites Look for in Your Products|
|3.2 Importance of Total Engagement, Reviews and Review Quality|
|3.3 Curating Great Reviews and Engagement|
|3.4 Patience: Algorithms Take Time to Reach Full Potential|
|3.5 How to Increase Your ‘Signals’|
|3.6 Advertising to Boost Recommendations|
|3.7 Recommending Your Own Products|
|3.8 Recommending Similar Products|
|3.9 How to Influence the Signals|