Idea of automation in digital marketing agency?

 

Automation in a digital marketing agency can refer to the use of technology and software tools to streamline and optimize various tasks and processes. Some examples of automation in a digital marketing agency may include:

 

Email marketing automation: Using tools to send personalized, automated emails to a large list of subscribers based on specific triggers, such as signing up for a newsletter or abandoning a shopping cart.

 

Social media automation: Scheduling and publishing social media posts in advance using tools like Hootsuite or Buffer.

 

Ad campaign automation: Using tools like Google Ads to set up and run automated ad campaigns based on specific targeting criteria and budget constraints.

 

SEO automation: Using tools like Ahrefs or SEMrush to automate keyword research, backlink analysis, and other SEO tasks.

 

 

 

 

Lead generation automation: Using tools like Leadformly or OptinMonster to create and publish customizable lead generation forms on a website, and then automating the process of capturing, storing, and following up with leads.

 

Content marketing automation: Using tools like HubSpot or Marketo to automate the distribution and promotion of blog posts, ebooks, and other content assets across various channels, such as social media, email, and paid advertising.

 

Website analytics and tracking automation: Using tools like Google Analytics to track and analyze website traffic and user behavior automatically, and then using that data to optimize marketing campaigns and improve the user experience.

 

Customer relationship management (CRM) automation: Using tools like Salesforce or Zoho CRM to manage and automate the process of tracking and interacting with customers, including tasks like lead scoring, segmentation, and personalized communication.

 

 

 

Landing page and form automation: Using tools like Unbounce or Leadpages to create and publish customizable landing pages and forms, and then automating the process of capturing and storing leads.

 

Influencer marketing automation: Using tools like Tribe or AspireIQ to automate the process of identifying, contacting, and collaborating with influencers on social media platforms.

 

Chatbot automation: Using tools like MobileMonkey or ManyChat to create and deploy chatbots on websites and social media platforms to automate customer interactions and support.

 

Marketing automation platform integration: Using tools like Zapier or Integromat to integrate various marketing automation tools and platforms, allowing for seamless communication and data transfer between different systems.

 

Reputation management automation: Using tools like Reputation.com or ReviewTrackers to automate the process of tracking and responding to online customer reviews and ratings across various platforms.

 

Personalization automation: Using tools like Qubit or Adobe Target to automate the process of delivering personalized content and experiences to website visitors based on their location, behavior, and other factors.

 

Lead nurturing automation: Using tools like Pardot or Act-On to automate the process of nurturing leads through the sales funnel with personalized communication and content based on their level of engagement and readiness to buy.

 

Event marketing automation: Using tools like Eventbrite or Cvent to automate the process of planning, promoting, and managing events, including tasks like registration, ticket sales, and email communication.

 

Customer segmentation automation: Using tools like Segment or Lytics to automate the process of dividing customers into different segments based on shared characteristics, allowing for more targeted and personalized marketing efforts.

 

Remarketing automation: Using tools like Google Ads or Facebook Ads to automate the process of targeting ads to website visitors who have previously shown interest in a product or service.

 

Customer service automation: Using tools like Zendesk or Freshdesk to automate the process of handling customer inquiries and complaints, including tasks like routing, prioritization, and resolution.

 

Video marketing automation: Using tools like Animoto or InVideo to automate the process of creating and editing professional-quality marketing videos, including tasks like selecting templates, adding images and text, and rendering the final product.

 

 

Overall, the goal of automation in a digital marketing agency is to save time, increase efficiency, and improve the accuracy and effectiveness of marketing campaigns. By automating certain tasks, digital marketers can focus on higher-level strategy and creative tasks, rather than getting bogged down in the details.

 

how to make sure mysql use more ram in window server

  find your .ini file and increase the limit in innodb_buffer_pool_size  and dont forget to restart the service. 

visual-studio-code-angular-node-prevent-debugger-from-stepping-into-library-cod

 https://code.visualstudio.com/updates/v1_8#_node-debugging 

https://code.visualstudio.com/updates/v1_8#_node-debugging 

How can I remove background from images using OpenCV python ?

import cv2

import numpy as np

#== Parameters =======================================================================

BLUR = 21

CANNY_THRESH_1 = 10

CANNY_THRESH_2 = 200

MASK_DILATE_ITER = 10

MASK_ERODE_ITER = 10

MASK_COLOR = (0.0,0.0,1.0) # In BGR format

#== Processing =======================================================================

#-- Read image -----------------------------------------------------------------------

img = cv2.imread('C:/Temp/person.jpg')

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

#-- Edge detection -------------------------------------------------------------------

edges = cv2.Canny(gray, CANNY_THRESH_1, CANNY_THRESH_2)

edges = cv2.dilate(edges, None)

edges = cv2.erode(edges, None)

#-- Find contours in edges, sort by area ---------------------------------------------

contour_info = []

_, contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)

# Previously, for a previous version of cv2, this line was: 

#  contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)

# Thanks to notes from commenters, I've updated the code but left this note

for c in contours:

    contour_info.append((

        c,

        cv2.isContourConvex(c),

        cv2.contourArea(c),

    ))

contour_info = sorted(contour_info, key=lambda c: c[2], reverse=True)

max_contour = contour_info[0]

#-- Create empty mask, draw filled polygon on it corresponding to largest contour ----

# Mask is black, polygon is white

mask = np.zeros(edges.shape)

cv2.fillConvexPoly(mask, max_contour[0], (255))

#-- Smooth mask, then blur it --------------------------------------------------------

mask = cv2.dilate(mask, None, iterations=MASK_DILATE_ITER)

mask = cv2.erode(mask, None, iterations=MASK_ERODE_ITER)

mask = cv2.GaussianBlur(mask, (BLUR, BLUR), 0)

mask_stack = np.dstack([mask]*3)    # Create 3-channel alpha mask

#-- Blend masked img into MASK_COLOR background --------------------------------------

mask_stack  = mask_stack.astype('float32') / 255.0          # Use float matrices, 

img         = img.astype('float32') / 255.0                 #  for easy blending

masked = (mask_stack * img) + ((1-mask_stack) * MASK_COLOR) # Blend

masked = (masked * 255).astype('uint8')                     # Convert back to 8-bit 

cv2.imshow('img', masked)                                   # Display

cv2.waitKey()

#cv2.imwrite('C:/Temp/person-masked.jpg', masked)           # Save

how to blur background using opencv python

    import cv2

import numpy as np

img = cv2.imread("C:/my_pics/rahul.png")
blurred_img = cv2.GaussianBlur(img, (21, 21), 0)

mask = np.zeros((512, 512, 3), dtype=np.uint8)
mask = cv2.circle(mask, (258, 258), 100, np.array([255, 255, 255]), -1)

out = np.where(mask==np.array([255, 255, 255]), img, blurred_img)

cv2.imwrite("./out.png", out)

Which datatype should I use in c# while SQL column is money type

 The decimal keyword indicates a 128-bit data type. Compared to floating-point types, the decimal type has more precision and a smaller range, which makes it appropriate for financial and monetary calculations.

You can use a decimal as follows:

decimal myMoney = 300.5m;

how to get total number of public properties in a class c#

 class MyClass

{  
    public string A { get; set; }
    public string B { get; set; }
    public string C { get; set; }

    public MyClass()
    {
        int count = this.GetType().GetProperties().Count();
        // or
        count = typeof(MyClass).GetProperties().Count();
    }
}