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How Genesys Enhances ABM with Real Purchase Intent from Priority Engine Sarah Geissler

Sr. Product Marketing Manager

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Challenge: Solution:

They use TechTarget’s Priority Engine account and prospect-level intent to better understand relevant and recent behavior of target accounts and buying teams researching their solutions outside of the Genesys domain.

Results: An interview with technology sales and marketing innovator, Fred Serpa, LATAM Regional Marketing Manager at Genesys

Genesys sells customer experience and contact center technology to mid-sized and enterprise businesses. Fred is responsible for marketing in LATAM, coordinating with the Global Marketing team and applying best practices regionally. Check him out on LinkedIn.

What are some challenges that you face specific to your marketing strategy at Genesys? How are you using Priority Engine as part of your ABM strategy?

Priority Engine is a great source of intent to help us better understand the behavior of the people researching our solutions outside of the Genesys domain. At Genesys, we are very focused on ABM campaigns and trying to find ways to accelerate our key accounts, and Priority Engine helps us achieve that. Our Priority Engine Account Lists are set up to reflect the same group of target accounts we are currently engaging in our first-party campaigns to expand our ABM audience’s intent to more than just first-party data.

It’s critical for both marketing and sales to understand how decision-makers are behaving. Priority Engine accomplishes that by identifying relevant insights for both sales and marketing to leverage.

It is critical for both marketing and sales to understand how decision-makers are behaving. Priority Engine accomplishes that by identifying relevant insights for both to leverage.”

Tell us about your tech stack and what a typical workflow looks like for your marketing and sales teams. How are you planning to leverage Priority Engine and Engagio together moving forward?

Our plan is to use Engagio as a centralized platform for all our different data sources to live together, including Priority Engine intent data. This will help our marketing and sales teams understand how our accounts and the people at those accounts are interacting with us.

What is your plan for leveraging Priority Engine intent as a part of your lead scoring strategy?

We use first, second and third-party intent data to help with our lead scoring. We really care about how people are engaging with us and how recently. Recent engagement is one of our key lead scoring metrics. If we know a lead from Priority Engine performed an action with us in the last week, that will impact the lead score. Just knowing someone downloaded a whitepaper isn’t enough. Priority Engine provides us with the tech topics a specific person is interested in, the specific content that person downloaded, and the timeframe in which they downloaded it.

How is Priority Engine helping you overcome your challenges and see success?

Before Priority Engine, it was challenging to build an audience based on only first-party intent. With Priority Engine, we can now see exactly what a person is looking at, easily understand the behavior at the person level, and decide if we want to include them in a campaign or event using relevant and recent information.

Tell us about your experience with the TechTarget Team?

The TechTarget team has been phenomenal. They have provided us the support we need, especially for LATAM. They helped set up our Account Lists in Priority Engine and are always providing us with the reporting and insights needed to further enhance our content syndication strategy.

A big thank you to Fred for sharing some feedback with us. We look forward to hearing about more of your wins using TechTarget products in the future!

If you’re interested in sharing your TechTarget story with us, feel free to reach out to me here.

Account-Based Marketing, Priority Engine, purchase intent data

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C++ Program To Implement Priority Queue

The queue which is implemented as FIFO where insertions are done at one end (rear) and deletions are done from another end (front). The first element that entered is deleted first.

Queue operations are

EnQueue (int data): Insertion at rear end

int DeQueue(): Deletion from front end

But a priority queue doesn’t follow First-In-First-Out, but rather than each element has a priority based on the basis of urgency.

Items with the same priority are processed on First-In-First-Out service basis.

An item with higher priority is processed before other items with lower priority.

Class Descriptions Begin    class Priority_Queue has following functions:    function insert() to insert items at priority queue with their priorities:       1) If queue is empty insert data from the left end of the queue.       2) If queue is having some nodes then insert the new node at the end of those nodes having priority          same with the new node and also before all the nodes having priority lesser than the          current priority of the new node.       function del() to delete items from queue.    If queue is completely empty, print underflow otherwise delete the front element and update front. using namespace std; struct n    int p;    int info;    struct n *l; }; class Priority_Queue {    private:             n *f;    public:       Priority_Queue()          f = NULL;       }       void insert(int i, int p) {          n *t, *q;          t = new n;             f = t;          } else {             q = f;          }       }       void del() {          n *t;          if(f == NULL)             cout<<"Queue Underflown";          else {             t = f;             free(t);          }       }       void show()          n *ptr;          ptr = f;          if (f == NULL)             cout<<"Queue is emptyn";          else {             cout<<"Queue is :n";             cout<<"Priority Itemn";             while(ptr != NULL) {             }          }       } }; int main() {    int c, i, p;    Priority_Queue pq;    Do//perform switch opeartion {       cout<<"1.Insertn";       cout<<"2.Deleten";       cout<<"3.Displayn";       cout<<"4.Exitn";       cout<<"Enter your choice : ";       switch(c) {          case 1:             cout<<"Input the item value to be added in the queue : ";             cout<<"Enter its priority : ";             pq.insert(i, p);             break;          case 2:             pq.del();             break;          case 3:             pq.show();             break;          case 4:             break;          default:          cout<<"Wrong choicen";       }    }    while(c != 4);    return 0; } Output 1.Insert 2.Delete 3.Display 4.Exit Enter your choice : 1 Input the item value to be added in the queue : 7 Enter its priority : 2 1.Insert 2.Delete 3.Display 4.Exit Enter your choice : 1 Input the item value to be added in the queue : 6 Enter its priority : 1 1.Insert 2.Delete 3.Display 4.Exit Enter your choice : 1 Input the item value to be added in the queue : 3 Enter its priority : 3 1.Insert 2.Delete 3.Display 4.Exit Enter your choice : 1 Input the item value to be added in the queue : 4 Enter its priority : 3 1.Insert 2.Delete 3.Display 4.Exit Enter your choice : 3 Queue is : Priority Item 1 6 2 7 3 3 3 4 1.Insert 2.Delete 3.Display 4.Exit Enter your choice : 4

Taskus Enhances Customer Experience Of Leading On

According to Statista, the online food delivery market is set to accelerate from nearly US$17 billion in 2023 to more than US$24 billion in 2023. To cope up with the industry growth, an on-demand food delivery company is transforming the way goods move within cities by enabling anyone to have anything – specifically restaurant favourites – delivered on-demand. This significant platform connects local couriers with customers which can deliver everything from batteries to a complete meal for a crowd within minimal amount of wait time.  

Business Challenge

With the growth of the company, the demand for high quality customer service was also at the peak. It was hard to match the influx of inquiries received during the lunch and dinner demand spikes which led to cancelled orders and refunds on inaccurate or late orders by the company. Subsequently, this marked direct impact of revenue of the company and drove low CSAT scores. To manage the non-peak performance became too difficult. Additionally, the non-urgent inquiries including changing a credit card after payment, explaining a delivery fee, and reporting minor missing items such as utensils, did not get the same resolution sensitivity. Hence the requests were severely backlogged in the system.  

The Solution

TaskUs studied the historical data to tackle workforce and volume issues. It then translated the data to actionable resolutions to optimise peak and non-peak efficiency. The service provider also hosted weekly meetings to review assumptions, handle items, productivity and SLAs by ticket type and volume. Further, to manage non-peak demand, TaskUs analysed the backlog of support tickets and discovered that about 60 percent of open tickets were the same 25 questions. Therefore, TaskUs bucketed these tickets, wrote scripted answers and systematically cleared the queue. Post that the remaining queue was way more manageable. The service provider developed a part-time employee program to subsidize its full time workforce during peak demand hours. This led to increase in orders and reduction in refunds for inaccurate or late orders by providing enough teammates during peak hours to assist customers.  

Results

According to Statista, the online food delivery market is set to accelerate from nearly US$17 billion in 2023 to more than US$24 billion in 2023. To cope up with the industry growth, an on-demand food delivery company is transforming the way goods move within cities by enabling anyone to have anything – specifically restaurant favourites – delivered on-demand. This significant platform connects local couriers with customers which can deliver everything from batteries to a complete meal for a crowd within minimal amount of wait chúng tôi the growth of the company, the demand for high quality customer service was also at the peak. It was hard to match the influx of inquiries received during the lunch and dinner demand spikes which led to cancelled orders and refunds on inaccurate or late orders by the company. Subsequently, this marked direct impact of revenue of the company and drove low CSAT scores. To manage the non-peak performance became too difficult. Additionally, the non-urgent inquiries including changing a credit card after payment, explaining a delivery fee, and reporting minor missing items such as utensils, did not get the same resolution sensitivity. Hence the requests were severely backlogged in the system.TaskUs studied the historical data to tackle workforce and volume issues. It then translated the data to actionable resolutions to optimise peak and non-peak efficiency. The service provider also hosted weekly meetings to review assumptions, handle items, productivity and SLAs by ticket type and volume. Further, to manage non-peak demand, TaskUs analysed the backlog of support tickets and discovered that about 60 percent of open tickets were the same 25 questions. Therefore, TaskUs bucketed these tickets, wrote scripted answers and systematically cleared the queue. Post that the remaining queue was way more manageable. The service provider developed a part-time employee program to subsidize its full time workforce during peak demand hours. This led to increase in orders and reduction in refunds for inaccurate or late orders by providing enough teammates during peak hours to assist chúng tôi provided efficiency positioned TaskUs to be more agile to real time volume, and to continue to scale as its clients’ business grows.

Difference Between Analytical Engine And Difference Engine

In this article, we will discuss the important differences between analytical engine and difference engine. But before discussing the differences, let us first discuss their basics.

What is a Difference Engine?

The difference engine is a mechanical computing machine developed by Charles Babbage in the 19th century. It was designed to calculate mathematical tables that were used in engineering and scientific computations.

The operation of the difference engine was based on the principle of finite differences. Finite differences are a concept in mathematics in which differences are determined between adjacent values in a table containing numbers.

Difference engine use the concept of finite differences to perform basic arithmetic operations such as addition, subtraction, multiplication, and division.

The first prototype of the difference engine consisted of a collection of gears and levers made of brass, and was released in 1822, and it laid the foundation for modern computers.

What is Analytical Engine?

The analytical engine is also a mechanical computing machine invented by Charles Babbage in the 19th century. The analytical engine was developed to perform complex operations like logarithmic and trigonometric functions, which could not be performed by the difference engine. Overall, the analytical engine was developed to be a general-purpose computing device that can perform any kind of mathematic operations.

The analytical engine makes use of punched cards to manipulate and store data. It consists of a mill that can perform operations like addition, subtraction, multiplication, division, logarithmic operations, and trigonometric functions.

The concept of conditional branching was used in the analytical engine that allows it to perform different calculations based on the results of previous calculations. The analytical engine also supports looping, allowing it to repeat a series of operations multiple times.

After getting insights into the basics of analytical engine and difference engine, let us now discuss all the important differences between them.

Difference between Analytical Engine and Difference Engine

The important differences between analytical engine and difference engine are listed in the following table:

S.No.

Difference Engine

Analytical Engine

1.

The difference engine is a mechanical computing device that was designed to perform basic arithmetic operations like addition, subtraction, multiplication, and division.

The analytical engine is also a mechanical computing device designed to be a general-purpose machine that could perform any kind of mathematical operations like arithmetic operations, logarithmic operations, trigonometric functions, etc.

2.

Difference engine is considered a simple mechanical calculator.

Analytical engine is considered as a general-purpose computing device.

3.

Difference engine was designed to calculate mathematical tables used in engineering and scientific applications.

Analytical engine was designed to perform any kind of operation used in general-purpose computing.

4.

Difference engine consists of a set of gears and levers made of brass to store and manipulate data.

Analytical engine consists of punched cards to store and manipulate data.

5.

Difference engine was invented in 1822 by the English mathematical Charles Babbage.

Analytical engine was invented in 1837 by Charles Babbage.

6.

Difference engine was powered by a hand crank.

Analytical engine was powered by steam.

7.

Difference engine does not support looping feature.

Analytical engine supports looping feature, allowing it to repeat a series of operations multiple times.

8.

Difference engine does not support conditional branching feature.

Analytical engine supports conditional branching, allowing it to perform different operations based on results of previous calculations.

9.

Difference engine is relatively less complex.

Analytical engine is more complex than difference engine.

10.

Difference engine is less costly than analytical engine.

Analytical engine is more expensive.

Conclusion

How To Set Process Priority In Task Manager On Windows 10

What exactly is process priority? Should you be making changes to it? And how do you actually set the process priority in Windows 10? This guide will answer all these questions.

Table of Contents

What Is Process Priority and Why Is It Important?

Computers aren’t multitaskers. Not really. When your operating system is running multiple programs (or just background services) simultaneously, it is actually juggling among them.

Process priority is simply the ‘importance’ of each process. Tasks that are essential for the smooth running of your computer (mostly system processes) are accorded a higher priority than an application running on top. This ensures that even under the maximum load, the core capabilities of your PC are not affected.

What Are the Process Priority Levels?

There are six priority levels in Windows. Only five of these are meant to be set by applications (or users, for that matter).

Normal is, well, the ‘normal’ priority level. Most applications run at this level.

Below normal is the priority level just below normal. Processes on this level are allocated fewer resources than normal applications. Best suited for unimportant tasks with no time constraints.

Low is the lowest priority level in Windows. Tasks operating at this level are given resources only after all other processes have completed their current tasks.

Above normal is the next higher priority level after normal. Use this for processes that need a little boost but don’t need to upstage system processes.

High is a priority level used by important system processes necessary for the smooth functioning of the computer. Not recommended for user applications.

Realtime is the highest possible priority level in Windows. Basically, tasks on this level run in real-time, at the expense of any and every other process. For this reason, this level is only reserved for hardware interfacing processes. Running applications on this priority level can easily crash your computer.

The normal and above normal are really the only two priority levels you should use for everyday tasks. Priority levels higher than that should be left to system processes and the lower levels for unimportant background tasks.

What Is the Effect of Setting the Priority of a Task?

Setting a new priority of a process modifies its place in the processing queue. Tasks with a higher priority are given preference in the allocation of system resources like CPU time and memory, allowing them to run faster.

On the flip side, too many tasks pushed to a higher priority level defeat the very purpose of there being a hierarchy in the first place. If every process is running at High, how is the operating system to determine which processes are truly essential?

If too many non-essential tasks are upgraded to higher priority levels, your computer might start freezing up or even crash outright. This is why in most cases the best idea is to leave the process priority as it is. Even when you do change the process priority, stick to small changes and apply them at only one or two processes.

How to Set Process Priority in Task Manager in Windows 10

While there are multiple ways to set process priority in Windows, the easiest method is to use the Task Manager.

On opening the Task Manager for the first time, you will be greeted with a barebones window showing just the running applications. Select More details to get the complete view.

Now you can see the complete list of all the running processes on your computer, including background tasks. By default they are sorted by memory consumption; you can select any other category from the top to change the sorting.

Select the process you want to change the priority of and switch to the Details tab.

In Details, you can view the status and other technical details of the running process. Many sub-processes hidden on the main screen are also shown here.

A prompt will appear, confirming whether you want to change the priority of the selected process. Select Change priority to apply the change.

This will set the new priority of the process immediately. The process will operate on this priority level for the rest of the current session. If you restart your computer (or just the process) the priority level will be reset to its default.

Should You Change the Priority of a Process?

We have seen how easy it is to change the priority level of a process from the Task Manager in Windows 10. This might make you wonder – Why not upgrade the priority of every running application? Surely boosting performance is always a good thing?

But you shouldn’t do that. There is a reason there are various priority levels in the first place, and putting every running process in the High category will only create conflicts and system instability.

3 Questions To Ask B2B Intent Data Providers

3 Questions to Ask B2B Intent Data Providers Andrew Briney

Chief Product Officer

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With all this potential, it’s no wonder the intent marketplace has exploded in recent months. Providers of external intent data include mature online media companies such as TechTarget as well as startups like Bombora, The Big Willow, MRP/Prelytix and others.

But intent data is not without its share of gotchas, which may require a huge leap of faith on your part when investing in lists of accounts these providers claim are heating up. When deciding whether to buy from any of these vendors, make sure to ask tough questions and push for maximum transparency.

Example: Acme Corp.

Let’s say an external intent data provider is telling you “Acme Corp.” is showing strong or increased intent activity around Flash Storage solutions. Ask them these questions:

Question 1: “You say Acme is investigating Flash Storage. How do you know it’s Acme?”

Challenge: For intent data to be useful you have to be confident the provider has accurately identified who’s truly behind the activity. Many providers rely on reverse IP lookup to identify “active” companies. That’s problematic because IP lookup can only resolve a fraction of IP addresses into accurate domain names, and even fewer outside of North America. Moreover, since IP addresses tend to change often, IP mapping tools easily go out of date, further undermining accuracy. In the end, the impact of all this is wasted spend, wasted effort and squandered internal momentum.

Recommendation: Look for providers who offer techniques beyond IP lookup for identifying accounts, such as direct user input into registration forms.

Question 2: “How do you know Acme’s interested in Flash Storage?”

Challenge: Since this data is being used to pinpoint real purchase intent, you also need to trust that the content used to produce the activity is actually related to your solution. Many providers “crawl the Web” searching for content with keyword tags associated to the market segment you specified (Flash Storage). When their machines locate such content, they’ll then do IP lookups on the accounts visiting the associated pages.

This all sounds super cool – machines finding relevant material for us all across the Web’s great blue ocean – until you consider that across the entire Web there simply isn’t that much highly focused, in-depth content on topics like Flash Storage, and even less that shows up high enough on search engines to drive material traffic volumes.

Recommendation: Ask providers for a specific understanding of the content sources (Web sites, Social Networks) they’re using to derive intent in your market area. Beware of solutions that don’t reveal the source of the content and user/account activity – it’s a warning sign they may be associating intent where none actually exists.

Question 3: “Who at Acme Corp. is investigating Flash Storage?”

Challenge: Assuming you can get to a place of confidence about the provider’s account list, think through how you want to leverage this data. A list of active accounts without named contacts restricts its usefulness to volume-oriented marketing activities like programmatic ad targeting. And while gains in ad performance are a good thing, for external intent data to deliver dramatic results it needs to have deeper, down-funnel applications. For that you need a corresponding list of the individual contacts — and not just any contacts, but those in tech decision roles with recent activity or expressed interest. (Of course, these contacts must also have opted in to being contacted by you!).

Recommendation: Ask the provider if they provide contact lists for the accounts they identify as active/in market. If they do, ask them the source of the contacts, and whether those contacts are “just names” or whether they are the actual people who generated the intent signals in the first place.

To learn more about how real purchase intent insight can significantly improve marketing efforts, fuel your pipeline and deliver better sales and marketing alignment, contact us today at [email protected].

b2b purchase intent insight, purchase intent data, purchase intent insight, technology purchase intent, TechTarget

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