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knowledgeiswealth · 10 days

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Linked In

is searching for an "active community of talent" so I'm going to beef up my profile in hopes of walking into my dream career. Follow me on LinkedIn if you want to watch :)

__________________________________________________________

(MAR-MAY 2024) Research

SERVICES MODE:

You can add up to 10 services you provide as a freelancer, in turn allowing you to be listed as a "similar profile" to other connections or users. Use this to sell your work!

CREATOR MODE & TOOLS:

When you switch your account to "Creator Mode" with LinkedIn, you are eligible for discovery. (This means you are suggested as a follow to those who follow or connect to similar profiles & connections.)

You are able to add a 30sec profile video, add a link to your intro section & add custom buttons. (Great tool for PROMO of goods & services.)

'Follow' button is an automatic update, but once you get an increase in follows (over 500), you have the option to switch to / or add the 'Connect' button. This requires users to request to connect with you and shows less on feed. (Important for your networking knowledge also*)

You also have access to the following features once you abided by the Community Policy Guidelines, account in good standing, account over 30 days old, have 150+ followers & recently shared any type of original content:

-Audio Events (i.e: live broadcasts & podcasts)

-Sending out your own newsletter to connections & a dedicated group of subscribers (huge game changer for businesses with customers on the platform - cuts out some email marketing!)

-Articles, Documents & Short Form Posts (these can be left to interpretation based on your goals for the platform)

-LinkedIn Live

PLAN OF ACTION:

Using the information above (& tips below) conduct a page audit top to bottom, editing your headline, URL, summary, and updating any changes to schooling or resume.

Use an auto scheduler if needed to CONSISTENTLY create POLISHED, SHORT-FORM CONTENT, IMGS, OR LINKS & interact, this will get you featured and increase activity based on hashtags, connections and engagement. Some posts that do well on this platform include but not limited to faceless content, resources, opportunities to rally for a cause, updates, wins/losses, interesting data and insights as you dive into projects.

Follow any brands, companies or creators you would like to work with. Study their engagement, CTA, hooks, niche, etc. *DO NOT COPY*

Daily or weekly, set aside 15minutes-1hour to read articles, look for jobs or do any professional/industry research. Search and keep an eye out for mentions or profiles similar to business you want to be in, follow those users and similar profiles (just in case they do not accept your request other mutual connections may allow you to see their posts & activity.) *Also review these users' posts, job histories and any connections, you can also look for job openings with any companies mentioned by clicking their pages!*

Tips & More Specific Details:

Best times to post as of 3/2024: Mon. & Fri. 8-4p, Tues. & Wed. 7-5p, Thurs. 7-4p, Sat. 6-3p & Sun. 8-2p.

You and other users can filter your feed by 'Top Updates' or 'Chronological' order *keep this in mind if timing is important for your posts.

You can use AI prompts to improve your headers & summaries.

Follow and view posts and resources on the LinkedIn Guide To Creating page for an idea of what this platform's algorithm likes & considers "quality content." (i.e: LinkedIn favors employee advocacy, so employee pictures, recognition and benefits are big for businesses of all sizes.)

Things this platform considers "spammy" include but not limited too many hooks, images, emojis or polls, chain mail, fake/excessive/irrelevant/repetitive questions.

The algorithm uses topics and keywords to highlight engaging & relevant conversations so use them any chance you get! More engagement = SPREAD (prioritize reach & shares!) Content on this platform is prioritized based on interaction. You can also use keyword finders (Like Google Keyword Planner) in conjunction with the search engine on LinkedIn to discover relevant mentions & hashtags (Max of 3 depending on length of post.) *For each hashtag, click to see how many people are following these - this will give you an idea of the current clicks, interaction, language, and interest in each topic! *A MAX OF 5 BRANDS/USERS PER POST*

CONSISTENTLY POSTING = a few posts per week then add more as engagement increases

The most popular hashtags on the platform as of APR 2024 are tagged below, hope this helps :) *UPDATING THROUGH MAY

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jcmarchi · 24 days

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Why data quality is critical for marketing in the age of GenAI

New Post has been published on https://thedigitalinsider.com/why-data-quality-is-critical-for-marketing-in-the-age-of-genai/

Why data quality is critical for marketing in the age of GenAI

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A recent survey reveals that CMOs around the world are optimistic and confident about GenAI’s future ability to enhance productivity and create competitive advantage. Seventy per cent are already using GenAI and 19 per cent are testing it. And the main areas they’re exploring are personalisation (67%), content creation (49%) and market segmentation (41%).

However, for many consumer brands, the divide between expectations and reality looms large. Marketers envisioning a seamless, magical customer experience must recognise that AI’s effectiveness depends on high-quality underlying data. Without that, the AI falls flat, leaving marketers grappling with a less-than-magical reality.

AI-powered marketing fail

Let’s take a closer look at what AI-powered marketing with poor data quality could look like. Say I’m a customer of a general sports apparel and outdoor store, and I’m planning for my upcoming annual winter ski trip. I’m excited to use the personal shopper AI to give me an experience that’s easy and customised to me.

I need to fill in some gaps in my ski wardrobe, so I ask the personal shopper AI to suggest some items to purchase. But the AI is creating its responses based on data about me that’s been scattered across the brand’s multiple systems. Without a clear picture of who I am, it asks me for some basic information that it should already know. Slightly annoying… I’m used to entering my info when I shop online, but I was hoping the AI upgrade to the experience would make things easier for me.

Because my data is so disconnected, the AI concierge only has an order associated with my name from two years ago, which was actually a gift. Without a full picture of me, this personal shopper AI is unable to generate accurate insights and ends up sharing recommendations that aren’t helpful.

Ultimately this subpar experience makes me less excited about purchasing from this brand, and I decide to go elsewhere.

The culprit behind a disconnected and impersonal generative AI experience is data quality — poor data quality = poor customer experience.

AI-powered marketing for the win

Now, let’s revisit this outdoor sports retailer scenario, but imagine that the personal shopper AI is powered by accurate, unified data that has a complete history of my interactions with the brand from first purchase to last return.

I enter my first question, and I get a super-personalised and friendly response, already starting to create the experience of a one-on-one connection with a helpful sales associate. It automatically references my shopping history and connects my past purchases to my current shopping needs.

Based on my prompts and responses, the concierge provides a tailored set of recommendations to fill in my ski wardrobe along with direct links to purchase. The AI is then able to generate sophisticated insights about me as a customer and even make predictions about the types of products I might want to buy based on my past purchases, driving up the likelihood of me purchasing and potentially even expanding my basket to buy additional items.

Within the experience, I am able to actually use the concierge to order without having to navigate elsewhere. I also know my returns or any future purchases will be incorporated into my profile.

Because it knew my history and preferences, Generative AI was able to create a buying experience for me that was super personalised and convenient. This is a brand I will keep returning to for future purchases.

In other words, when it comes to AI for marketing, better data = better results.

So how do you actually address the data quality challenge? And what could that look like in this new world of AI?

Solving the data quality problem

The critical first element to powering an effective AI strategy is a unified customer data foundation. The tricky part is that accurately unifying customer data is hard due to its scale and complexity — most consumers have at least two email addresses, have moved over eleven times in their lifetimes and use an average of five channels (or if they are millennials or Gen Z, it’s actually twelve channels).

Many familiar approaches to unifying customer data are rules-based and use deterministic/fuzzy matching, but these methods are rigid and break down when data doesn’t match perfectly. This, in turn, creates an inaccurate customer profile that can actually miss a huge portion of a customer’s lifetime history with the brand and not account for recent purchases or changes of contact information.

A better way to build a unified data foundation actually involves using AI models (a different flavour of AI than generative AI for marketing) to find the connections between data points to tell if they belong to the same person with the same nuance and flexibility of a human but at massive scale.

When your customer data tools can use AI to unify every touchpoint in the customer journey from first interaction to last purchase and beyond (loyalty, email, website data, etc…), the result is a comprehensive customer profile that tells you who your customers are and how they interact with your brand.

How data quality in generative AI drives growth

For the most part, marketers have access to the same set of generative AI tools, therefore, the fuel you input will become your differentiator.

Data quality to power AI provides benefits in three areas:

Customer experiences that stand out — more personalised, creative offers, better customer service interactions, a smoother end-to-end experience, etc.

Operational efficiency gains for your teams — faster time to market, less manual intervention, better ROI on campaigns, etc.

Reduced compute costs — better-informed AI doesn’t need to go back and forth with the user, which saves on racking up API calls that quickly get expensive

As generative AI tools for marketing continue to evolve, they bring the promise of getting back to the level of one-to-one personalisation that customers would expect in their favourite stores, but now at a massive scale. That won’t happen on its own, though — brands need to provide AI tools with accurate customer data to bring the AI magic to life.

The dos and don’ts of AI in marketing

AI is a helpful sidekick to many industries, especially marketing — as long as it’s leveraged appropriately. Here’s a quick ‘cheat-sheet’ to help marketers on their GenAI journey:

Do:

Be explicit about the specific use cases where you plan to use data and AI and specify the expected outcomes. What results do you expect to achieve?

Carefully evaluate if Gen AI is the most appropriate tool for your specific use case.

Prioritise data quality and comprehensiveness — establishing a unified customer data foundation is essential for an effective AI strategy.

Don’t:

Rush to implement GenAI across all areas. Start with a manageable, human-in-the-loop use case, such as generating subject lines.

(Editor’s note: This article is sponsored by Amperity)

Tags: ai, data, genai, generative ai, marketing

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maxisdezign · 1 month

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Ai Pattern

HIDE THE ANNOYING TOOL BAR:

Press the 3 dots of the right side of the bar press 'hide bar'

CHANGE SWATCHES SIZE:

To change the view of my swatches menu, press the ham burger menu this will appear and then press 'large thumbnail view' to see the swatches bigger, and not smaller.

MAKE THE PATTERN:

Draw something with pen tool (in the example I made a shield/scale shape Fill this drawing with white fill and a black stroke.

Put a black box fill black no stroke box around the drawn shape.

Then select both the drawn shape and the box.

Then drag the selected into the swatches menu, this create the pattern. I can now fill anything with my pattern.

A pattern will be shown as anything that I put inside the black square / Anything selected into the swatches menu.

FILLING THE PATTERN: I made a curvy shape to paste my pattern into using the pen tool. (IMG1)

Then click into the curvy made shape with the move tool (v) and select the pattern i've made from the swatches menu. (IMG2)

Double click the pattern in the swatches panel to see the pattern options, this will allow me to change the offset of the shapes, and type of shape it is etc... (IMG3)

This works for more than just squares. After making a pattern from a square, we then made another one from a hexagon. Where I put my scale/shield shape into a black hexagon, made it into its own swatch, and then added the pattern to a shape. By going into the Pattern Options, I can also offset the placement of the hexagons. (IMG 4)

ARTBOARDS:

Select artboard tool Select old art board and drag it out Hold shift + option it will create new art board

EXPORTING:

Before exporting image pattern to InDesign must go object -> expand!

Then command + c from The pattern file, and in InDesign press command + v to paste it.

REFLECTION:

I found the process quite simple to follow, and it was easy to pick it up. I enjoyed learning how to make patterns, and this will definitely become useful in the future. If anything, I wish I had tried it with something more interesting than a shield/scale, but I'm still proud of how it turned out, especially the hexagon one looks extra nice with the white line around the shape. Next steps: I want to practice making patterns again but with much more complicated pattern designs.

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realdatascraping · 2 months

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How to Discover Lazada API Data Sets - A Complete Guide.

https://www.realdataapi.com/assets/img/blog/lazada-api-datasets-guide/intro.png

Introduction

In today's data-driven world, access to vast and diverse datasets is a cornerstone of innovation and informed decision-making. One such valuable resource is Lazada API data sets, offering a wealth of information from one of Southeast Asia's leading e-commerce platforms. In this comprehensive guide, we will show you how to effectively discover, leverage, and harness the power of Lazada data when you Scrape Lazada API Dataset.

Lazada, a part of the Alibaba Group, boasts a significant presence across multiple countries, making it a treasure trove of e-commerce data. From product listings to customer reviews and sales trends, these data sets provide invaluable insights into consumer behavior, market dynamics, and emerging trends within the e-commerce landscape.

This guide is designed to cater to both newcomers and seasoned data enthusiasts. Whether you're an e-commerce entrepreneur looking to gain a competitive edge or a data analyst seeking to unlock the potential of Lazada API Data Scraper, this step-by-step guide will empower you with the knowledge and skills needed to navigate this vast reservoir of information effectively.

Throughout this journey, we'll explore the various types of data sets available, delve into practical use cases, and provide you with the tools and techniques required to access and utilize Lazada API data sets to their full potential. So, let's embark on this enlightening voyage into the realm of Lazada's data, where possibilities and insights await discovery.

Importance of Lazada as a Prominent E-Commerce Marketplace

Lazada stands as a prominent and influential player in the realm of e-commerce, solidifying its importance through several key factors:

Market Reach: Lazada's extensive presence spans multiple Southeast Asian countries, including Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam. This expansive reach provides businesses with access to a vast and diverse consumer base, making it an attractive marketplace for both local and international sellers.

Diverse Product Range: Lazada offers a wide array of products, ranging from consumer electronics and fashion to groceries and household goods. This diverse product range caters to the evolving needs and preferences of its customers, positioning it as a one-stop destination for online shopping.

Ecosystem Integration: As part of the Alibaba Group, Lazada enjoys seamless integration with Alibaba's ecosystem, enabling cross-border trade and access to a wealth of resources, including logistics and financial services. This integration facilitates the growth and expansion of businesses using the platform.

Mobile-Centric Approach: Lazada has embraced the mobile revolution, with user-friendly mobile apps and a mobile-first approach. This caters to the increasing number of shoppers who prefer to browse and purchase products on their smartphones, enhancing the overall shopping experience.

E-commerce Innovation: Lazada continually invests in technology and innovation, incorporating features like live streaming, social commerce, and AI-driven recommendations. These innovations enhance the user experience and provide sellers with cutting-edge tools to engage customers.

Local Expertise: Operating in diverse Southeast Asian markets requires an understanding of local culture, preferences, and nuances. Lazada's localized approach and on-ground presence allow it to adapt to each market, making it a trusted platform among consumers.

Lazada's significance as a prominent e-commerce marketplace is underscored by its extensive market reach, diverse product offerings, ecosystem integration, mobile-centric approach, commitment to innovation, and localized expertise. These factors collectively make Lazada a vital platform for businesses seeking to tap into the thriving e-commerce landscape of Southeast Asia.

Importance of Lazada API for Developers

Data Accessibility: Lazada API provides developers with direct access to a wealth of e-commerce data, including product listings, pricing information, customer reviews, and sales statistics. This data is invaluable for market research, trend analysis, and competitive intelligence.

Order Processing: The API facilitates order management, allowing developers to retrieve orders, update order statuses, and handle customer inquiries seamlessly. This streamlines the fulfillment process and enhances customer satisfaction.

Automated Marketing: Developers can use the API to automate marketing activities, such as creating and scheduling promotions, sending personalized recommendations to customers, and tracking the effectiveness of marketing campaigns.

Integration Capabilities: Lazada API can be integrated with various third-party tools and systems, including inventory management software, CRM systems, and analytics platforms. This integration streamlines business operations and data synchronization.

Customization: Developers have the flexibility to customize and tailor the e-commerce experience to meet specific business needs. This includes creating unique storefronts, implementing custom search algorithms, and designing user-friendly interfaces.

Scalability: As businesses grow, the Lazada API can scale accordingly to handle increased data volume and traffic. This scalability ensures that the e-commerce platform remains robust and responsive.

Global Reach: The API facilitates cross-border trade, enabling businesses to expand their reach beyond their home markets. Developers can leverage the API to manage international sales and logistics efficiently.

Real-time Updates: Lazada API provides real-time updates on product availability, pricing changes, and customer feedback. This real-time information empowers businesses to make informed decisions quickly.

The Lazada API empowers developers to create, enhance, and optimize e-commerce experiences, from managing inventory and processing orders to implementing data-driven marketing strategies. Its versatility and integration capabilities make it an indispensable tool for businesses looking to thrive in the dynamic and competitive e-commerce landscape.

Navigating Lazada's API Ecosystem: Understanding the Range of Integration Opportunities

Lazada offers various types of APIs (Application Programming Interfaces) to cater to different aspects of e-commerce operations. These APIs provide developers with the tools and data necessary to enhance the Lazada shopping experience. Here are some of the key types of Lazada APIs:

Product API

Product Information: This API allows developers to access detailed product information, including titles, descriptions, pricing, images, and availability. It is essential for creating product listings and managing inventory.

Category Information: Developers can retrieve category information to help organize and categorize products effectively within the platform.

Order API

Order Management: The Order API enables developers to retrieve and manage customer orders. This includes retrieving order details, updating order statuses, and handling returns and refunds.

Shipping and Fulfillment: Developers can use this API to manage shipping and fulfillment processes, ensuring timely delivery of orders to customers.

User and Authentication API

User Authentication: This API provides user authentication and authorization services, allowing developers to create secure user accounts, handle login/logout, and manage user profiles.

User Information: Developers can access user information, such as user profiles, preferences, and order history, to provide personalized shopping experiences.

Marketing and Promotions API

Promotion Management: This API allows developers to create and manage promotions, discounts, and coupon campaigns to attract and retain customers.

Recommendation Engine: Developers can implement recommendation algorithms to suggest personalized product recommendations to users, increasing cross-selling and upselling opportunities.

Review and Rating API

Customer Reviews: This API provides access to customer reviews and ratings for products. Developers can display reviews on product pages and use sentiment analysis for insights.

Seller Ratings: Developers can retrieve seller ratings and feedback to assess the reputation of sellers on the platform.

Analytics and Reporting API

Sales Analytics: This API provides access to sales data, revenue reports, and performance metrics. Developers can use this data for business intelligence and decision-making.

Traffic and Conversion Analytics: Developers can access data on website traffic, user behavior, and conversion rates to optimize the shopping experience.

Logistics and Shipping API

Shipping Partners Integration: Lazada offers APIs for integrating with various logistics and shipping partners to facilitate order fulfillment and tracking.

Inventory Management: Developers can manage inventory levels, track shipments, and optimize logistics operations using these APIs.

Payment and Financial API

Payment Gateway Integration: This API allows developers to integrate payment gateways for secure and seamless transactions.

Financial Reporting: Developers can access financial data, transaction history, and revenue reports to monitor financial performance.

These various types of Lazada APIs empower developers to create, enhance, and optimize different aspects of the e-commerce platform, providing a comprehensive and seamless shopping experience for both sellers and customers.

Different Uses of Lazada API Data Sets

When you Scrape Lazada Data it offers various applications and use cases for businesses and developers looking to leverage e-commerce data. Here are different ways these data sets can be utilized:

Product Listing and Management

Lazada API data sets enable sellers to list and manage their products efficiently. You can create, update, and optimize product listings, ensuring accurate and appealing product information.

Inventory Management

Easily keep track of product stock levels.

Automatically update inventory availability.

Receive notifications when products are running low.

Price Optimization

Access real-time pricing information to adjust product prices dynamically based on market demand and competition, helping you stay competitive and maximize profits.

Order Fulfillment

Seamlessly process customer orders.

Automate order confirmation.

Manage order status updates, leading to efficient order fulfillment and improved customer satisfaction.

Customer Insights

Analyze customer behavior, preferences, and purchase history to personalize marketing strategies, enhance customer engagement, and increase retention rates.

Market Research

Access historical and real-time market data to identify trends, consumer preferences, and emerging markets, aiding in informed business decisions and product development.

Competitor Analysis

Monitor competitor activities, pricing strategies, and product offerings to refine your competitive edge and marketing tactics.

Sales Performance Tracking

Utilize data sets to track sales performance, revenue trends, and profitability across different product categories and geographic regions.

Customer Reviews and Ratings

Aggregate and analyze customer reviews and ratings to improve product quality, customer service, and reputation management.

Marketing Campaigns

Create targeted marketing campaigns using customer data, purchase history, and behavioral insights to optimize ad spend and increase conversion rates.

Supply Chain Management

Streamline logistics, warehousing, and shipping processes by integrating Lazada API data sets with third-party logistics providers and supply chain systems.

Cross-Selling and Upselling

Implement recommendation algorithms based on customer behavior to suggest complementary products and increase average order value.

Fraud Prevention

Detect and prevent fraudulent transactions using data analytics and real-time monitoring, enhancing payment security and reducing chargebacks.

Customer Support

Enhance customer support services with access to customer data, order history, and inquiries, enabling faster issue resolution and improved customer satisfaction.

Reporting and Analytics

Generate detailed reports and perform in-depth data analysis to gain actionable insights into business performance, enabling data-driven decision-making.

International Expansion

Use Lazada API data sets to assess market potential in different countries and regions, facilitating international expansion strategies.

How Real Data API Can Help in Scraping Lazada API Data Sets Data?

Real Data API offers a comprehensive suite of services and expertise to assist businesses in efficiently scraping and utilizing Lazada API data sets. Here's how Real Data API can be instrumental in this process:

Data Scraping Tools: Real Data API utilizes state-of-the-art web scraping tools and technologies to extract data from Lazada's API. Their tools are designed to handle large volumes of data efficiently and accurately.

Data Quality Assurance: Ensuring data accuracy and quality is paramount. Real Data API employs data validation and cleaning techniques to guarantee that the scraped data is reliable and error-free.

Customized Data Extraction: Real Data API tailors the data extraction process to meet your business needs. Whether you require product information, pricing data, customer reviews, or other data points, they can configure the scraping process accordingly.

Real-time Data Updates: Real Data API can set up automated processes for regular data updates, ensuring you can always access the latest information from Lazada's API.

Data Transformation and Enrichment: Real Data API can transform and enrich the scraped data to make it more actionable. This includes data formatting, categorization, and creating custom data structures as needed.

Data Storage and Management: Real Data API provides solutions for efficiently storing and managing scraped data, including database setup, data archiving, and retrieval mechanisms.

Data Security: Data security is a top priority. Real Data API implements robust security measures to protect the integrity and confidentiality of your scraped data.

Data Analysis and Reporting: Beyond scraping, Real Data API can assist in analyzing the data and generating reports or dashboards to extract actionable insights for your business.

Custom Software Development: If your project requires custom software or applications to interact with Lazada's API, Real Data API can develop and deploy such solutions to meet your unique requirements.

Compliance and Best Practices: Real Data API adheres to ethical web scraping practices and ensures compliance with Lazada's API usage policies and terms of service.

Ongoing Support: Real Data API provides ongoing support and maintenance to address any issues, updates, or enhancements required for your scraping project.

By leveraging Real Data API' expertise, businesses can harness the full potential of Lazada's API data sets, from web scraping to data integration and analysis, ultimately driving informed decision-making and improving e-commerce operations.

Conclusion

Real Data API offers a robust solution for businesses harnessing the power of Lazada's API data sets. By partnering with Real Data API, you can unlock a world of possibilities, from accessing real-time e-commerce data to optimizing your operations and making data-driven decisions. With Real Data API' expertise in API integration, data scraping, and data management, you can navigate the complexities of Lazada's API seamlessly and efficiently.

Take advantage of the opportunities that Lazada's API data sets can bring to your business. Take the first step towards data-driven success today. Contact Real Data API and embark on a journey of discovery and growth.

Discover the potential of Lazada API data sets with Real Data API – Your path to e-commerce excellence begins here.

Know More: https://www.realdataapi.com/lazada-api-datasets-guide.php

#ScrapeLazadaAPIDataset #ScrapingLazadaAPIDataSets #LazadaAPIDataScraper #LazadaAPIDataCollection #ExtractLazadaAPIDataSet #WebScrapingAPIServices

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hemihr12005 · 2 months

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W1D1 fundies: 1 (software/pūmanawa)

We started to learn more about the differences in-between vector and raster. Vector is drawn lines that form a illustration (usually on PS), these type of illustrations don't lose quality if you zoom in. Raster are pixelated illustrations (usually on Ai) and if you zoom in loses its clean lines and is obviously pixelated, so it is not the best way of making a logo or illustration for a large image. Raster is better suited for images with lots of colours that aren't going to be enlarged (better suited for photos).

We then set up our tumblr accounts, which we will be using to post what we learn every class.

folder stytem:

Hannah Hemi:

project name:

PRJ= project files

IMG= image files (image files: photos, sketches, reference pics etc.)

DOC= documents (any format: cleint brief. vcleint feeback, docment data files, asset lists etc.)

OUT= output folder (pdfs for projects drafts and final pdf go in this folder)

command N for folders = new finder window

save first file in project file with 00 before hand (in renaming), then next one can be 01 and it will make ur files be in chronological order.

illustrator commands

z = zoom (or command+) (drag right or left on z to zoom in or out)

space = pan

/ = clear fill/stroke (stroke is the border, fill is the inside)

x = toggle (swap) fill/stroke

p = pen (get out of pen without closin shape is COMMAND click)

v = selection tool (full arrow = full shape - select all)

A = direct selection tool (hollow arrow = one part - a peice of the shape) (or hold command click)

move, rotate and scale are known as transform

using skills learnt in session:

the illustrator version.

for the first shape i just used pen tool and tried to make sure all the lines stayed all in a line and that the triangle were symmetrical to each other. since the shape wasn't a closed shape i used A tool to click out of using pen tool.

for he diamond i tire to use the guides illustrator has when using the pen tool to make it symmetrical.

for the third shape i drew the shape without the gap first and then used a tool to add anchors in the path allowed me to remove part of the line.

for the fourth shape i used pen tool (P) and then shift to make sure my lines stayed straight and then i tried to make the spacing accurate to the drawings we were given.

for the fifth shape i drew a symmetrical triangle and again used A to make anchors so i could remove part of the path and then i drew the inside spiral part of the triangle, trying to stay symmetrical to the outer triangle shape.

the last shape i created one line with the pen tool and then copied the line so all the lines wee the same length and then i used object - transform - rotate and rotated the lines so they were all on the right angle.

It was fun to try make the shapes and pretty easy to do with all the tools we learnt today

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mobilephonetechnology · 2 months

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(2024-02-18 imge ©sophos) The mobile companies have schemes to alert users when a call looks suspicious. And personally these must do a reasonable job as I get fewer such caalls. But the other day I did get a call from a company wanting to talk about my THREE account. They did have details, but said they were working for THREE. I stopped the call, although I think it may have been genuine. This goes to show that we do need better nuisance caller software to reject more of these calls so we can be more confident that calls coming through are genuine.

From my statistical back ground any method needs to minimise type 1 and type 2 errors. That is limit the number of calls that get through which are nuisance calls, as well as limiting the number if rejected calls that are real. It is very difficult to do this. As if you focus on limiting the false positives (calls that get through) you will increase the number of false negatives (rejecting the real calls).

All the networks have software to detect scam calls. Recently O2 have become the second network after EE to adopt Hiya's technology that is based on AI. It is good to see the networks developing their software in this area.

The system will being used by EE and instaalled by O2 will detect scamer texts as well as calls.

#mobilephonetechnology #o2 #scammers

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speedyposts · 3 months

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Owner.com grabs $33M Series B to improve online guest experiences for mom-and-pop restaurants

Independent restaurant owners used to heavily rely on foot traffic as their way of marketing. In 2020, the global pandemic changed all that.

Overnight, restaurants needed to set up online ordering, have a plan for pick-up and delivery and find new ways to get in front of customers no longer going out to eat.

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Dabiri-Erewa warns Nigerians against irregular migration, Especially to Canada

The Nigerians in Diaspora Commission (NiDCOM), Abike Dabiri-Erewa, has urged Nigerians travelling abroad to go legitimately and with proper documentation

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Inspired by his mother’s struggles to attract customers to her dog grooming business, Adam Guild teamed up with Dean Bloembergen to create Owner.com to help independent restaurant owners better manage their online presence.

“People are hurting worse than ever in the restaurant industry because the inflation has created rising labor costs and rising food costs,” Guild told TechCrunch. “It’s compressing the already low profit margins of these restaurant owners, so it is more important to them than ever to figure out ways to increase sales and save money.”

To that end, Owner.com offers an all-in-one platform for restaurants that includes online ordering, a website builder, customer relationship management tools, marketing automation and a branded mobile app generator.

Owner.com whips up new tools for independent restaurants following funding

Restaurant sales were poised to reach sales of $997 billion in 2023, according to the National Restaurant Association. That provides huge opportunities for companies like Owner.com, Guild said.

There’s also room for other startups to leverage technology with tools focused on mom-and-pop restaurants. Last year, Superorder raised $10 million to help restaurants with their online presence, and there are dozens of companies with operations tools to manage both the front and back of the house, including Zitti, MarginEdge, OneOrder and TouchBistro.

To differentiate itself more, Owner.com recently tapped into artificial intelligence for new features, including an email marketer. As he described it, restaurant owners can start typing in a sentence of what they want the email to say or do. For example, “Tell my customers about my new yellow curry,” and the AI will produce an email for them designed in their style, written in their tone and ready to go out to customers.

Today, the company has thousands of customers after tripling the number in the past year. Owner processes hundreds of millions of dollars annually for its customers and yields tens of millions in revenue, Guild said.

Dean Bloembergen and Adam Guild, co-founders of Owner.com. (Image credit: Owner.com)

TechCrunch has followed Owner.com as it attracted $10.7 million in seed funding, led by SaaStr Fund, then $15 million in Series A capital led by Altman Capital.

Now the company raised $33 million in Series B funding on a $200 million post-money valuation, Guild said. Existing investors Redpoint Ventures and Altman Capital co-led the round with participation from Horsley Bridge, Activant Capital and Transpose Platform Management. Total capital raised is now $58.7 million.

Guild expects to continue investing in engineering teams and design teams to cater to what his customers are saying they need. In addition to the AI-powered email marketer, there are other tools in the pipeline.

“Even just five years ago, it used to be enough to provide great food and great service because those things are hard to do on their own,” Guild said. “It’s no longer enough if you want to be a successful restaurant. More of the guest experience has shifted online, even where people discover restaurants. Large corporations can afford to spend billions of dollars on teams of engineers and marketers and ad spend. Independent restaurant owners are being screwed over. What we are building is to help these mom-and-pop owners not only survive as a result of this technological change, but continue to thrive as more of their business goes online.”

As startups whip up a restaurant tech frenzy, is anyone close to Toast?

Dabiri-Erewa warns Nigerians against irregular migration, Especially to Canada

The Nigerians in Diaspora Commission (NiDCOM), Abike Dabiri-Erewa, has urged Nigerians travelling abroad to go legitimately and with proper documentation

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govindhtech · 6 months

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Motorola’s Moto G Power 5G: Bigger and Better in 2024

Render photos of a new Moto G Power 5G, the most recent iteration of which was released by Motorola in April 2023, have been leaked by OnLeaks. According to the credible leaker, the Moto G Power 5G (2024) would have dimensions of 167.3 x 76.4 x 8.5 mm, which would place it in a position that is marginally superior to the one that is now available. To be more specific, the Moto G Power 5G would have grown 4 millimeters higher and 2 millimeters broader between generations based on these specs.

The next Motorola Moto G Power 5G has seen some of its early render photos made public by a well-known leaker. Moto G Power 5G (2024) is likely to be bigger, with a larger display, lower bezels, and a more refined look.

With a 6.7-inch display, the Moto G Power 5G (2024) is 0.2 inches bigger than its predecessor. According to OnLeaks photos, Motorola has added smaller top and bottom bezels to this smartphone to modernize it. In addition to this, the Moto G Power 5G will have flat sides as opposed to the beveled finish that its predecessor had.

With an inbuilt 5G modem, the Mediatek Dimensity 930 is a quick mid-range system on a chip. It has six power-efficient Cortex-A55 cores running at up to 2 GHz (Octa-Core with Heterogeneous Multi-Processing) and two quick ARM Cortex-A78 cores running at up to 2.2 GHz. In addition, the chip incorporates an AI processing unit, an LPDDR5 / LPDDR4X memory controller, an IMG BXM-8-256 GPU, a Wi-Fi 5 modem, and video de- and encoding.

The 5G modem is compatible with dual SIM, mixed duplex (TDD/FDD), and NR 2CC. Up to 2.77 Gbit/s may be achieved in download rates.

The Dimensity 920 has a better GPU but a slower clocked CPU than the 930.

Made with the most recent 6nm technology, the Dimensity 930 is expected to have exceptionally high power efficiency.

In spite of this, Motorola was able to squeeze in enough room to install a 3.5 mm connector. This jack is located next to a microphone hole, a USB Type-C port, and a speaker that faces downward. Other information, such as whether Motorola will change the MediaTek Dimensity 930 processor, 5,000 mAh battery, 120 Hz display, or 50 MP camera found in the current Moto G Power 5G, remain unclear as of this writing, unfortunately.