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Sintel MP4 Surround 5.1 Full
13 mai 2011, par
Mis à jour : Février 2012
Langue : English
Type : Video
Autres articles (56)
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Publier sur MédiaSpip
13 juin 2013Puis-je poster des contenus à partir d’une tablette Ipad ?
Oui, si votre Médiaspip installé est à la version 0.2 ou supérieure. Contacter au besoin l’administrateur de votre MédiaSpip pour le savoir -
Des sites réalisés avec MediaSPIP
2 mai 2011, parCette page présente quelques-uns des sites fonctionnant sous MediaSPIP.
Vous pouvez bien entendu ajouter le votre grâce au formulaire en bas de page. -
Support audio et vidéo HTML5
10 avril 2011MediaSPIP utilise les balises HTML5 video et audio pour la lecture de documents multimedia en profitant des dernières innovations du W3C supportées par les navigateurs modernes.
Pour les navigateurs plus anciens, le lecteur flash Flowplayer est utilisé.
Le lecteur HTML5 utilisé a été spécifiquement créé pour MediaSPIP : il est complètement modifiable graphiquement pour correspondre à un thème choisi.
Ces technologies permettent de distribuer vidéo et son à la fois sur des ordinateurs conventionnels (...)
Sur d’autres sites (5503)
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Conversion Rate Optimisation Statistics for 2024 and Beyond
21 novembre 2023, par Erin — Analytics TipsDriving traffic to your website is only half the battle. The real challenge — once you’ve used a web analytics solution to understand how users behave — is turning more of those visitors into customers.
That doesn’t happen by accident. You need to employ conversion rate optimisation strategies and tools to see even a small lift in conversion rates. The good news is that it doesn’t take much to see massive results. Raising your conversion rate from 1% to 3% can triple your revenue.
In even better news, you don’t have to guess at the best ways to improve your conversion rate. We’ve done the hard work and collected the most recent and relevant conversion rate optimisation statistics to help you.
General conversion rate optimisation statistics
It appears the popularity of conversion rate optimisation is soaring. According to data collected by Google Trends, there were more people searching for the term “conversion rate optimization” in September 2023 than ever before.
As you can see from the chart below, the term’s popularity is on a clear upward trajectory, meaning even more people could be searching for it in the near future. (Source)
Do you want to know what the average landing page conversion rate is ? According to research by WordStream, the average website conversion rate across all industries is 2.35%.
That doesn’t paint the whole picture, however. Better-performing websites have significantly higher conversion rates. The top 25% of websites across all industries convert at a rate of 5.31% or higher. (Source)
Let’s break things down by industry now. The Unbounce Conversion Benchmark Report offers a detailed analysis of how landing pages convert across various industries.
First, we have the Finance and Insurance industry, which boasts a conversion rate of 15.6%.
On the other end, agencies appears to be one of the worst-performing. Agencies’ landing pages convert at a rate of 8.8%. (Source)
What about the size of the conversion rate optimisation industry ? Given the growth in popularity of the term in Google, surely the industry is experiencing growth, right ?
You’d be correct in that assumption. The conversion rate optimisation software market was valued at $771.2 million in 2018 and is projected to reach $1.932 billion by 2026 — a compound annual growth rate (CAGR) of 9.6%.
Statistics on the importance of conversion rate optimisation
If you’re reading this article, you probably think conversion rate optimisation is pretty important. But do you know its importance and where it ranks in your competitors’ priorities ? Read on to find out.
Bounce rate — the number of people who leave your website without visiting another page or taking action — is the scourge of conversion rate optimisation efforts. Every time someone bounces from your site, you lose the chance to convert them.
The questions, then, are : how often do people bounce on average and how does your bounce rate compare ?
Siege Media analysed over 1.3 billion sessions from a range of traffic sources, including 700 million bounces, to calculate an average bounce rate of 50.9%. (Source)
Bounce rates vary massively from website to website and industry to industry, however. Siege Media’s study unveils an array of average bounce rates across industries :
- Travel – 82.58%
- B2B – 65.17%
- Lifestyle – 64.26%
- Business and Finance – 63.51%
- Healthcare – 59.50%
- eCommerce – 54.54%
- Insurance – 45.96%
- Real Estate – 40.78%
It won’t come as much of a surprise to learn that marketers are determined to reduce bounce rates and improve lead conversion. Today’s marketers are highly performance-based. When asked about their priorities for the coming year, 79% of marketers said their priority was generating quality qualified leads — the most popular answer in the survey. (Source)
Just because it is a priority for marketers doesn’t mean that everyone has their stuff together. If you have a conversion rate optimisation process in place, you’re in the minority. According to research by HubSpot, less than one in five marketers (17%) use landing page A/B tests to improve their conversion rates. (Source)
When it comes to personalisation strategies – a common and effective tool to increase conversion rates — the picture isn’t any rosier. Research by Salesforce found just over one-quarter of markets are confident their organisation has a successful strategy for personalisation. (Source)
Conversion rate optimisation tactics statistics
There are hundreds of ways to improve your website’s conversion rates. From changing the color of buttons to the structure of your landing page to your entire conversion funnel, in this section, we’ll look at the most important statistics you need to know when choosing tactics and building your own CRO experiments.
If you are looking for the best method to convert visitors, then email lead generation forms are the way to go, according to HubSpot. This inoffensive and low-barrier data collection method boasts a 15% conversion rate, according to the marketing automation company’s research. (Source)
Where possible, make your call-to-actions personalised. Marketing personalisation, whether through behavioral segmentation or another strategy, is an incredibly powerful way of showing users that you care about their specific needs. It’s no great surprise, then, that HubSpot found personalised calls-to-actions perform a whopping 202% better than basic CTAs. (Source)
If you want to boost conversion rates, then it’s just as important to focus on quantity as well as quality. Yes, a great-looking, well-written landing page will go a long way to improving your conversion rate, but having a dozen of these pages will do even more.
Research by HubSpot found companies see a 55% increase in leads when they increase the number of landing pages from 10 to 15. What’s more, companies with over 40 landing pages increase conversion by more than 500%. (Source)
User-generated content (UGC) should also be high on your priority list to boost conversion rates. Several statistics show how powerful, impactful and persuasive social proof like user reviews can be.
Research shows that visitors who scroll to the point where they encounter user-generated content increase the likelihood they convert by a staggering 102.4%. (Source)
Other trust signs can be just as impactful. Research by Trustpilot found that the following four trust signals make consumers more likely to make a purchase when shown on a product page :
- Positive star rating and reviews (85% more likely to make a purchase)
- Positive star rating (78%)
- Positive customer testimonials (82%)
- Approved or authorised seller badge (76%)
(Source)
Showing ratings and reviews has also increased conversion rates by 38% on home appliances and electronics stores. (Source)
And no wonder, given that consumers are more likely to buy from brands they trust than brands they love, according to the 2021 Edelman Trust Barometer Special Report. (Source)
A lack of trust is also one of the top four reasons consumers abandon their shopping cart at checkout. (Source)
Traffic source conversion rate statistics
What type of traffic works the best when it comes to conversions, or how often you should be signing up users to your mailing list ? Let’s look at the stats to find out.
Email opt-ins are one of the most popular methods for collecting customer information — and an area where digital marketers spend a lot of time and effort when it comes to conversion rate optimisation. So, what is the average conversion rate of an email opt-in box ?
According to research by Sumo — based on 3.2 billion users who have seen their opt-in boxes — the average email opt-in rate is 1.95%. (Source)
Search advertising is an effective way of driving website traffic, but how often do those users click on these ads ?
WordStream’s research puts the average conversion of search advertising for all industries at 6.11%. (Source)
The arts and entertainment industry enjoys the highest clickthrough rates (11.78%), followed by sports and recreation (10.53%) and travel (10.03%). Legal services and the home improvement industry have the lowest clickthrough rates at 4.76% and 4.8%, respectively.
(Source) If you’re spending money on Google ads, then you’d better hope a significant amount of users convert after clicking them.
Unfortunately, conversion rates from Google ads decreased year-on-year for most industries in 2023, according to research by WordStream — in some cases, those decreases were significant. The only two industries that didn’t see a decrease in conversion rates were beauty and personal care and education and instruction. (Source)
The average conversion rate for search ads across all industries is 7.04%. The animal and pet niche has the highest conversion rate (13.41%), while apparel, fashion and jewelry have the lowest conversion rate (1.57%). (Source)
What about other forms of traffic ? Well, there’s good reason to try running interstitial ads on smartphone apps if you aren’t already. Ads on the iOS app see a 14.3 percent conversion rate on average. (Source)
E-commerce conversion rate optimisation statistics (400 words)
Conversion rate optimisation can be the difference between a store that sets new annual sales records and one struggling to get by.
The good news is that the conversion rate among US shoppers was the highest it’s ever been in 2021, with users converting at 2.6%. (Source)
If you have a Shopify store, then you may find conversion rates a little lower. A survey by Littledata found the average conversion rate for Shopify was 1.4% in September 2022. (Source)
What about specific e-commerce categories ? According to data provided by Dynamic Yield, the consumer goods category converted at the highest rate in September 2023 (4.22%), a spike of 0.34% from August.
Generally, the food and beverage niche boasts the highest conversion rate (4.87%), and the home and furniture niche has the lowest conversion rate (1.44%). (Source)
If you’re serious about driving sales, don’t focus on mobile devices at the expense of consumers who shop on desktop devices. The conversion rate among US shoppers tends to be higher for desktop users than for mobile users.
In the second quarter of 2022, for instance, desktop shoppers converted at a rate of 3% on average compared to smartphone users who converted at an average rate of 2%. (Source)
Increase your conversions with Matomo
Conversion rate optimisation can help you grow your subscriber list, build your customer base and increase your revenue. Now, it’s time to put what you’ve learned into practice.
Use the advice above to guide your experiments and track everything with Matomo. Achieve unparalleled data accuracy while harnessing an all-in-one solution packed with essential conversion optimisation features, including Heatmaps, Session Recordings and A/B Testing. Matomo makes it easier than ever to analyse conversion-focused experiments.
Get more from your conversion rate optimisations by trying Matomo free for 21 days. No credit card required.
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Getting and decoding video by RTP H264
29 novembre 2023, par AlekseiKraevParsing RTP H264.
WINAPI C. A queue from C++ has been applied, I repent.


RTP is generated using FFMPEG with the following command :
ffmpeg.exe -f gdigrab -framerate 25 -i desktop -s 853x480 -b:v 120000 -c:v libx264 -f rtp rtp ://127.0.0.1:8080


Parsing the incoming RTP/h264 stream and converting it to an RGB matrix.


video_H264_decode.h


#pragma once
#ifndef _VIDEO_H264_DECODE_SEND_H // Блокируем повторное включение этого модуля
#define _VIDEO_H264_DECODE_SEND_H
//******************************************************************************
// Section include
//******************************************************************************
#include "main.h"
#include 
//******************************************************************************
// Constants
//******************************************************************************

//******************************************************************************
// Type
//******************************************************************************
typedef struct {
 unsigned char* data;
 int size;
}RTPData_DType;

typedef struct 
{
 union
 {
 struct
 {
 char V:2; //Версия
 char P:1; //заполнение
 char X:1; //расширение
 char CC:4; //количество CSRC

 char M:1; //маркер (флаг последнего пакета AU),
 char PT:7; //полезная нагрузка (тип данных носителя полезной нагрузки RTP, H264 = 96)

 short sequence_number; //Порядковый номер: порядковый номер пакета RTP, увеличенный на 1.
 int time_stamp; //временная метка выборки медиа. 
 int SSRC; //Пакет данных имеет одинаковое происхождение.
 };
 unsigned char data[12];
 };
}RTPHeader_DType;
//******************************************************************************
// Global var
//******************************************************************************

//******************************************************************************
// Local function prototype
//******************************************************************************
UCHAR rtp_H264_recive_init(void);
UCHAR RTPStop(void);
//******************************************************************************
// Macros
//******************************************************************************
#define BYTE2_SWAP(X) ((((short)(X) & 0xff00) >> 8) |(((short)(X) & 0x00ff) << 8))
#endif
//******************************************************************************
// ENF OF FILE
//******************************************************************************


video_H264_decode.c


//******************************************************************************
//include
//******************************************************************************
#include "main.h"
/*#include "video_H264_decode.h"
#include 
#include 
#include <chrono>
#include 

#pragma comment(lib, "ws2_32.lib")
#include */
#include <iostream>
#include <queue>

extern "C" {
#include "libavformat/avformat.h"
#include "libavfilter/avfilter.h"
#include "libavdevice/avdevice.h"
#include "libswscale/swscale.h"
#include "libswresample/swresample.h"
#include "libpostproc/postprocess.h"
#include "libavcodec/avcodec.h"
}

#pragma comment(lib,"avcodec.lib")
#pragma comment(lib,"avdevice.lib")
#pragma comment(lib,"avfilter.lib")
#pragma comment(lib,"avformat.lib")
#pragma comment(lib,"avutil.lib")
#pragma comment(lib,"postproc.lib")
#pragma comment(lib,"swresample.lib")
#pragma comment(lib,"swscale.lib")

#pragma warning(disable: 4996)
//******************************************************************************
// Section for determining the variables used in the module
//******************************************************************************
//------------------------------------------------------------------------------
// Global
//------------------------------------------------------------------------------

//------------------------------------------------------------------------------
// Local
//------------------------------------------------------------------------------
const int inteval = 0x01000000;
BOOL FlagRTPActive = TRUE;

HANDLE hMutexRTPRecive;
HANDLE hSemaphoreRTP;
HANDLE hTreadRTPRecive;
HANDLE hTreadRTPDecode;


SOCKET RTPSocket; //socket UDP RTP
RTPData_DType packet;
RTPData_DType FU_buffer = { 0 };

std::queue q;
std::set<int> seq;

AVFormatContext* pAVFormatContext;
AVCodecContext* pAVCodecContext;
const AVCodec* pAVCodec;
AVFrame* pAVFrame;
AVFrame* AVFrameRGG;
SwsContext* pSwsContext;
AVPacket *pAVPacket;
AVCodecParserContext* pAVCodecParserContext;

UINT port;
//******************************************************************************
// Section of prototypes of local functions
//******************************************************************************
DWORD WINAPI rtp_H264_recive_Procedure(CONST LPVOID lpParam);
DWORD WINAPI rtp_decode_Procedure(CONST LPVOID lpParam);
char RTPSocketInit(void);
void RTPPacketParser(void);
char RTPSocketRecive(void);
void Decode_NaluToAVFrameRGG();
//******************************************************************************
// Section of the description of functions
//******************************************************************************
UCHAR rtp_H264_recive_init(void)
{
 hSemaphoreRTP = CreateSemaphore(
 NULL, // default security attributes
 0, // initial count
 1, // maximum count
 NULL); // unnamed semaphore

 hMutexRTPRecive = CreateMutex(
 NULL, // default security attributes
 FALSE, // initially not owned
 NULL); // unnamed mutex

 hTreadRTPRecive = CreateThread(NULL, NULL, rtp_H264_recive_Procedure, NULL, NULL, NULL);
 hTreadRTPDecode = CreateThread(NULL, NULL, rtp_decode_Procedure, NULL, NULL, NULL);

 return 0;
}
//------------------------------------------------------------------------------
UCHAR RTPStop(void)
{
 FlagRTPActive = FALSE;

 if (hSemaphoreRTP) CloseHandle(hSemaphoreRTP);
 if (hMutexRTPRecive) CloseHandle(hMutexRTPRecive);
 if (hTreadRTPRecive) CloseHandle(hTreadRTPRecive);

 closesocket(RTPSocket); 

 return 0;
}
//------------------------------------------------------------------------------
DWORD WINAPI rtp_H264_recive_Procedure(CONST LPVOID lpParam)
{
 while (RTPSocketInit() == 0)
 Sleep(2000);
 
 while (1)
 {
 RTPSocketRecive();
 RTPPacketParser();
 ReleaseSemaphore(hSemaphoreRTP, 1, NULL);
 }
}
//------------------------------------------------------------------------------
DWORD WINAPI rtp_decode_Procedure(CONST LPVOID lpParam)
{
 port = param.Option.VideoPort;

 pAVPacket = av_packet_alloc();
 if (!pAVPacket)
 {
 MessageBox(NULL, L"ERROR Could not allocate pAVPacket", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 }
 av_init_packet(pAVPacket);

 /* find the MPEG-1 video decoder */
 pAVCodec = avcodec_find_decoder(AV_CODEC_ID_H264);
 if (!pAVCodec)
 {
 MessageBox(NULL, L"ERROR Codec not found", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 }

 pAVCodecParserContext = av_parser_init(pAVCodec->id);
 if (!pAVCodecParserContext)
 {
 MessageBox(NULL, L"ERROR Parser not found", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 }

 pAVCodecContext = avcodec_alloc_context3(pAVCodec);
 if (!pAVCodecContext) 
 {
 MessageBox(NULL, L"ERROR Could not allocate video codec context", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 }
 
 if (avcodec_open2(pAVCodecContext, pAVCodec, NULL) < 0)
 {
 MessageBox(NULL, L"ERROR Could not open codec", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 }

 pAVFrame = av_frame_alloc();
 if (!pAVFrame) 
 {
 MessageBox(NULL, L"ERROR Could not allocate video frame", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 } 
 
 while (FlagRTPActive)
 {
 if(port != param.Option.VideoPort)
 closesocket(RTPSocket);

 WaitForSingleObject(hSemaphoreRTP, 500); 
 Decode_NaluToAVFrameRGG();
 }

 avformat_free_context(pAVFormatContext);
 av_frame_free(&pAVFrame);
 avcodec_close(pAVCodecContext);
 av_packet_free(&pAVPacket);

 
 if (hTreadRTPDecode) CloseHandle(hTreadRTPDecode);

 return 0;
}

//------------------------------------------------------------------------------
char RTPSocketInit(void)
{ 
 sockaddr_in RTPSocketAddr;
 
 RTPSocketAddr.sin_family = AF_INET;
 RTPSocketAddr.sin_addr.s_addr = htonl(INADDR_ANY);
 RTPSocketAddr.sin_port = htons(param.Option.VideoPort);

 RTPSocket = socket(AF_INET, SOCK_DGRAM, IPPROTO_UDP);
 if (RTPSocket == INVALID_SOCKET)
 {
 MessageBox(NULL, L"ERROR Invalid RTP Socket", L"UDP Socket", MB_OK | MB_ICONERROR);
 return 0;
 }

 int option = 12000;
 if (setsockopt(RTPSocket, SOL_SOCKET, SO_RCVBUF, (char*)&option, sizeof(option)) < 0)
 {
 printf("setsockopt failed\n");

 }

 /*option = TRUE;
 if (setsockopt(RTPSocket, SOL_SOCKET, SO_CONDITIONAL_ACCEPT, (char*)&option, sizeof(option)) < 0)
 {
 printf("setsockopt failed\n");

 }*/

 if (bind(RTPSocket, (sockaddr*)&RTPSocketAddr, sizeof(RTPSocketAddr)) == SOCKET_ERROR)
 {
 MessageBox(NULL, L"ERROR bind", L"UDP Socket", MB_OK | MB_ICONERROR);
 closesocket(RTPSocket);
 return 0;
 }
 return 1;
}

//------------------------------------------------------------------------------
char RTPSocketRecive(void)
{
 static char RecvBuf[2000];
 static int BufLen = 2000;

 int iResult = 0;
 struct sockaddr_in SenderAddr;
 int SenderAddrSize = sizeof(SenderAddr);
 TCHAR szErrorMsg[100];

 iResult = recvfrom(RTPSocket, RecvBuf, BufLen, 0, NULL, NULL);
 if (iResult == SOCKET_ERROR && FlagRTPActive == TRUE)
 {
 StringCchPrintf(szErrorMsg, 100, L"ERROR recvfrom Ошибка:%d", WSAGetLastError());
 MessageBox(NULL, szErrorMsg, L"UDP Socket", MB_OK | MB_ICONERROR);
 return -1;
 }

 packet.data = (unsigned char*)RecvBuf;
 packet.size = iResult;

 return 1;
}

//------------------------------------------------------------------------------
void RTPPacketParser(void)
{
 RTPHeader_DType RTPHeader;
 RTPData_DType NALU;
 unsigned char* buffer = packet.data;
 int pos = 0;
 static int count = 0;
 static short lastSequenceNumber = 0xFFFF;
 short type;
 char payload_header;

 //read rtp header
 memcpy(&RTPHeader, buffer, sizeof(RTPHeader));
 RTPHeader.sequence_number = BYTE2_SWAP(RTPHeader.sequence_number);
 pos += 12; 
 
 if (RTPHeader.X) {
 //profile extension
 short define;
 short length;
 length = buffer[pos + 3];//suppose not so long extension
 pos += 4;
 pos += (length * 4);
 }

 payload_header = buffer[pos];
 type = payload_header & 0x1f; //Тип полезной нагрузки RTP
 pos++;
 
 //STAP-A
 if (type == 24)
 { 
 while (pos < packet.size)
 {
 unsigned short NALU_size;
 memcpy(&NALU_size, buffer + pos, 2);
 NALU_size = BYTE2_SWAP(NALU_size);
 pos += 2;
 char NAL_header = buffer[pos];
 short NAL_type = NAL_header & 0x1f;

 if (NAL_type == 7) 
 {
 count++;
 //cout<<"SPS, sequence number: "</cout<<"PPS, sequence number: "</cout<<"end of sequence, sequence number: "< 0) 
 {
 NALU.data = (unsigned char*) malloc(NALU_size + 4);
 NALU.size = NALU_size + 4;
 memcpy(NALU.data, &inteval, 4);
 memcpy(NALU.data + 4, &buffer[pos], NALU_size);

 WaitForSingleObject(hMutexRTPRecive, INFINITE);
 q.push(NALU);
 ReleaseMutex(hMutexRTPRecive);
 }

 pos += NALU_size;
 }
 }
 //FU-A Fragmentation unit
 else if (type == 28)
 { 
 //FU header
 char FU_header = buffer[pos];
 bool fStart = FU_header & 0x80;
 bool fEnd = FU_header & 0x40;

 //NAL header
 char NAL_header = (payload_header & 0xe0) | (FU_header & 0x1f);
 short NAL_type = FU_header & 0x1f;
 if (NAL_type == 7) 
 {
 count++;
 //SPS
 }
 else if (NAL_type == 8) 
 {
 //PPS
 }
 else if (NAL_type == 10) 
 {
 //end of sequence
 }
 pos++;

 int size = packet.size - pos;
 
 if (count > 0)
 {
 if (fStart) 
 {
 if (FU_buffer.size != 0)
 {
 free(FU_buffer.data);
 FU_buffer.size = 0;
 }
 FU_buffer.data = (unsigned char*)malloc(size + 5);
 if (FU_buffer.data == NULL)
 return;
 FU_buffer.size = size + 5;
 memcpy(FU_buffer.data, &inteval, 4);
 memcpy(FU_buffer.data + 4, &NAL_header, 1);
 memcpy(FU_buffer.data + 5, buffer + pos, size);
 }
 else
 {
 unsigned char* temp = (unsigned char*)malloc(FU_buffer.size + size);
 memcpy(temp, FU_buffer.data, FU_buffer.size);
 memcpy(temp + FU_buffer.size, buffer + pos, size);
 if (FU_buffer.size != 0) free(FU_buffer.data);
 FU_buffer.data = temp;
 FU_buffer.size += size;
 }

 if (fEnd)
 {
 NALU.data = (unsigned char*)malloc(FU_buffer.size);
 NALU.size = FU_buffer.size;
 memcpy(NALU.data, FU_buffer.data, FU_buffer.size);

 WaitForSingleObject(hMutexRTPRecive, INFINITE);
 q.push(NALU);
 ReleaseMutex(hMutexRTPRecive);

 free(FU_buffer.data);
 FU_buffer.size = 0;
 }
 }
 
 }
 else 
 {
 //other type
 short NAL_type = type;
 if (NAL_type == 7) 
 {
 count++;
 //SPS
 }
 else if (NAL_type == 8) 
 {
 //PPS
 }
 else if (NAL_type == 10) 
 {
 //end of sequence
 }

 int size = packet.size - pos + 1;
 if (count > 0)
 {
 NALU.data = (unsigned char*)malloc(size+4);
 NALU.size = size + 4;
 memcpy(NALU.data, &inteval, 4);
 memcpy(NALU.data + 4, &buffer[12], size);

 WaitForSingleObject(hMutexRTPRecive, INFINITE);
 q.push(NALU);
 ReleaseMutex(hMutexRTPRecive);
 }
 }
}

//------------------------------------------------------------------------------
void Decode_NaluToAVFrameRGG()
{
 unsigned char cntNALU;
 int len = 0;
 static int size = 0;
 unsigned char* data = NULL;
 int ret;
 RTPData_DType NALU;

 av_frame_unref(pAVFrame);
 av_packet_unref(pAVPacket);

 while(1)
 {
 WaitForSingleObject(hMutexRTPRecive, INFINITE);
 if (q.empty())
 {
 ReleaseMutex(hMutexRTPRecive);
 break;
 }
 NALU = q.front();
 q.pop();
 ReleaseMutex(hMutexRTPRecive);

 data = NALU.data;
 size = NALU.size;

 while(size)
 { 
 len = av_parser_parse2(pAVCodecParserContext, pAVCodecContext, &pAVPacket->data, &pAVPacket->size,
 (uint8_t*)data, size,
 AV_NOPTS_VALUE, AV_NOPTS_VALUE, AV_NOPTS_VALUE);

 data = len ? data + len : data;
 size -= len;
 
 if (pAVPacket->size)
 {
 ret = avcodec_send_packet(pAVCodecContext, pAVPacket);

 if(ret == AVERROR_EOF)
 MessageBox(NULL, L"the codec has been fully flushed, and there will be no more output frames", L"avcodec_send_packet", MB_OK | MB_ICONERROR);

 if (ret < 0)
 {
 MessageBox(NULL, L"ERROR sending a packet for decoding", L"Decode", MB_OK | MB_ICONERROR);
 //exit(1);
 }

 while (ret >= 0) 
 {
 ret = avcodec_receive_frame(pAVCodecContext, pAVFrame);
 if (ret == AVERROR(EAGAIN) || ret == AVERROR_EOF)
 break;
 else if (ret < 0) {
 MessageBox(NULL, L"ERROR during decoding", L"Decode", MB_OK | MB_ICONERROR);
 //exit(1);
 }
 
 AVFrameRGG = av_frame_alloc(); 
 pSwsContext = sws_getContext(pAVCodecContext->width, pAVCodecContext->height, pAVCodecContext->pix_fmt,
 pAVCodecContext->width, pAVCodecContext->height, AV_PIX_FMT_RGB24, SWS_SPLINE,
 0, 0, 0);

 sws_scale_frame(pSwsContext, AVFrameRGG, pAVFrame);
 
 ImgBufferSet(AVFrameRGG->data[0], pAVCodecContext->height, pAVCodecContext->width, AVFrameRGG->linesize[0]);

 sws_freeContext(pSwsContext);
 av_frame_free(&AVFrameRGG);
 }
 }
 }
 free(NALU.data);
 NALU.size = 0;
 } 
}

</int></queue></iostream></chrono>

It's DECIDED


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What is Audience Segmentation ? The 5 Main Types & Examples
16 novembre 2023, par Erin — Analytics TipsThe days of mass marketing with the same message for millions are long gone. Today, savvy marketers instead focus on delivering the most relevant message to the right person at the right time.
They do this at scale by segmenting their audiences based on various data points. This isn’t an easy process because there are many types of audience segmentation. If you take the wrong approach, you risk delivering irrelevant messages to your audience — or breaking their trust with poor data management.
In this article, we’ll break down the most common types of audience segmentation, share examples highlighting their usefulness and cover how you can segment campaigns without breaking data regulations.
What is audience segmentation ?
Audience segmentation is when you divide your audience into multiple smaller specific audiences based on various factors. The goal is to deliver a more targeted marketing message or to glean unique insights from analytics.
It can be as broad as dividing a marketing campaign by location or as specific as separating audiences by their interests, hobbies and behaviour.
Audience segmentation inherently makes a lot of sense. Consider this : an urban office worker and a rural farmer have vastly different needs. By targeting your marketing efforts towards agriculture workers in rural areas, you’re honing in on a group more likely to be interested in farm equipment.
Audience segmentation has existed since the beginning of marketing. Advertisers used to select magazines and placements based on who typically read them. They would run a golf club ad in a golf magazine, not in the national newspaper.
How narrow you can make your audience segments by leveraging multiple data points has changed.
Why audience segmentation matters
In a survey by McKinsey, 71% of consumers said they expected personalisation, and 76% get frustrated when a vendor doesn’t deliver.
These numbers reflect expectations from consumers who have actively engaged with a brand — created an account, signed up for an email list or purchased a product.
They expect you to take that data and give them relevant product recommendations — like a shoe polishing kit if you bought nice leather loafers.
If you don’t do any sort of audience segmentation, you’re likely to frustrate your customers with post-sale campaigns. If, for example, you just send the same follow-up email to all customers, you’d damage many relationships. Some might ask : “What ? Why would you think I need that ?” Then they’d promptly opt out of your email marketing campaigns.
To avoid that, you need to segment your audience so you can deliver relevant content at all stages of the customer journey.
5 key types of audience segmentation
To help you deliver the right content to the right person or identify crucial insights in analytics, you can use five types of audience segmentation : demographic, behavioural, psychographic, technographic and transactional.
Demographic segmentation
Demographic segmentation is when you segment a larger audience based on demographic data points like location, age or other factors.
The most basic demographic segmentation factor is location, which is easy to leverage in marketing efforts. For example, geographic segmentation can use IP addresses and separate marketing efforts by country.
But more advanced demographic data points are becoming increasingly sensitive to handle. Especially in Europe, GDPR makes advanced demographics a more tentative subject. Using age, education level and employment to target marketing campaigns is possible. But you need to navigate this terrain thoughtfully and responsibly, ensuring meticulous adherence to privacy regulations.
Potential data points :
- Location
- Age
- Marital status
- Income
- Employment
- Education
Example of effective demographic segmentation :
A clothing brand targeting diverse locations needs to account for the varying weather conditions. In colder regions, showcasing winter collections or insulated clothing might resonate more with the audience. Conversely, in warmer climates, promoting lightweight or summer attire could be more effective.
Here are two ads run by North Face on Facebook and Instagram to different audiences to highlight different collections :
Each collection is featured differently and uses a different approach with its copy and even the media. With social media ads, targeting people based on advanced demographics is simple enough — you can just single out the factors when making your campaign. But if you don’t want to rely on these data-mining companies, that doesn’t mean you have no options for segmentation.
Consider allowing people to self-select their interests or preferences by incorporating a short survey within your email sign-up form. This simple addition can enhance engagement, decrease bounce rates, and ultimately improve conversion rates, offering valuable insights into audience preferences.
This is a great way to segment ethically and without the need of data-mining companies.
Behavioural segmentation
Behavioural segmentation segments audiences based on their interaction with your website or app.
You use various data points to segment your target audience based on their actions.
Potential data points :
- Page visits
- Referral source
- Clicks
- Downloads
- Video plays
- Goal completion (e.g., signing up for a newsletter or purchasing a product)
Example of using behavioural segmentation to improve campaign efficiency :
One effective method involves using a web analytics tool such as Matomo to uncover patterns. By segmenting actions like specific clicks and downloads, pinpoint valuable trends—identifying actions that significantly enhance visitor conversions.
For instance, if a case study video substantially boosts conversion rates, elevate its prominence to capitalise on this success.
Then, you can set up a conditional CTA within the video player. Make it pop up after the user has watched the entire video. Use a specific form and sign them up to a specific segment for each case study. This way, you know the prospect’s ideal use case without surveying them.
This is an example of behavioural segmentation that doesn’t rely on third-party cookies.
Psychographic segmentation
Psychographic segmentation is when you segment audiences based on your interpretation of their personality or preferences.
Potential data points :
- Social media patterns
- Follows
- Hobbies
- Interests
Example of effective psychographic segmentation :
Here, Adidas segments its audience based on whether they like cycling or rugby. It makes no sense to show a rugby ad to someone who’s into cycling and vice versa. But to rugby athletes, the ad is very relevant.
If you want to avoid social platforms, you can use surveys about hobbies and interests to segment your target audience in an ethical way.
Technographic segmentation
Technographic segmentation is when you single out specific parts of your audience based on which hardware or software they use.
Potential data points :
- Type of device used
- Device model or brand
- Browser used
Example of segmenting by device type to improve user experience :
Upon noticing a considerable influx of tablet users accessing their platform, a leading news outlet decided to optimise their tablet browsing experience. They overhauled the website interface, focusing on smoother navigation and better readability for tablet users. These changes offered tablet users a seamless and enjoyable reading experience tailored precisely to their device.
Transactional segmentation
Transactional segmentation is when you use your customers’ purchase history to better target your marketing message to their needs.
When consumers prefer personalisation, they typically mean based on their actual transactions, not their social media profiles.
Potential data points :
- Average order value
- Product categories purchased within X months
- X days since the last purchase of a consumable product
Example of effective transactional segmentation :
A pet supply store identifies a segment of customers consistently purchasing cat food but not other pet products. They create targeted email campaigns offering discounts or loyalty rewards specifically for cat-related items to encourage repeat purchases within this segment.
If you want to improve customer loyalty and increase revenue, the last thing you should do is send generic marketing emails. Relevant product recommendations or coupons are the best way to use transactional segmentation.
B2B-specific : Firmographic segmentation
Beyond the five main segmentation types, B2B marketers often use “firmographic” factors when segmenting their campaigns. It’s a way to segment campaigns that go beyond the considerations of the individual.
Potential data points :
- Company size
- Number of employees
- Company industry
- Geographic location (office)
Example of effective firmographic segmentation :
Companies of different sizes won’t need the same solution — so segmenting leads by company size is one of the most common and effective examples of B2B audience segmentation.
The difference here is that B2B campaigns are often segmented through manual research. With an account-based marketing approach, you start by researching your potential customers. You then separate the target audience into smaller segments (or even a one-to-one campaign).
Start segmenting and analysing your audience more deeply with Matomo
Segmentation is a great place to start if you want to level up your marketing efforts. Modern consumers expect to get relevant content, and you must give it to them.
But doing so in a privacy-sensitive way is not always easy. You need the right approach to segment your customer base without alienating them or breaking regulations.
That’s where Matomo comes in. Matomo champions privacy compliance while offering comprehensive insights and segmentation capabilities. With robust privacy controls and cookieless configuration, it ensures GDPR and other regulations are met, empowering data-driven decisions without compromising user privacy.
Take advantage of our 21-day free trial to get insights that can help you improve your marketing strategy and better reach your target audience. No credit card required.
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